
<span id="api"></span><h1><span class="yiyi-st" id="yiyi-1104">API参考</span></h1>
        <blockquote>
        <p>原文：<a href="http://pandas.pydata.org/pandas-docs/stable/api.html">http://pandas.pydata.org/pandas-docs/stable/api.html</a></p>
        <p>译者：<a href="https://github.com/wizardforcel">飞龙</a> <a href="http://usyiyi.cn/">UsyiyiCN</a></p>
        <p>校对：（虚位以待）</p>
        </blockquote>
    
<div class="section" id="input-output">
<span id="api-functions"></span><h2><span class="yiyi-st" id="yiyi-1105">输入//输出</span></h2>
<div class="section" id="pickling">
<h3><span class="yiyi-st" id="yiyi-1106">清洗</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1107"><a class="reference internal" href="generated/pandas.read_pickle.html#pandas.read_pickle" title="pandas.read_pickle"><code class="xref py py-obj docutils literal"><span class="pre">read_pickle</span></code></a>（path）</span></td>
<td><span class="yiyi-st" id="yiyi-1108">从指定的加载pickled pandas对象（或任何其他pickled对象）</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="flat-file">
<h3><span class="yiyi-st" id="yiyi-1109">Flat File</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1110"><a class="reference internal" href="generated/pandas.read_table.html#pandas.read_table" title="pandas.read_table"><code class="xref py py-obj docutils literal"><span class="pre">read_table</span></code></a>（filepath_or_buffer [，sep，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1111">将一般分隔文件读入DataFrame</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1112"><a class="reference internal" href="generated/pandas.read_csv.html#pandas.read_csv" title="pandas.read_csv"><code class="xref py py-obj docutils literal"><span class="pre">read_csv</span></code></a>（filepath_or_buffer [，sep，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1113">将CSV（逗号分隔）文件读入DataFrame</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1114"><a class="reference internal" href="generated/pandas.read_fwf.html#pandas.read_fwf" title="pandas.read_fwf"><code class="xref py py-obj docutils literal"><span class="pre">read_fwf</span></code></a>（filepath_or_buffer [，colspecs，width]）</span></td>
<td><span class="yiyi-st" id="yiyi-1115">将固定宽度格式的行的表读入DataFrame</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1116"><a class="reference internal" href="generated/pandas.read_msgpack.html#pandas.read_msgpack" title="pandas.read_msgpack"><code class="xref py py-obj docutils literal"><span class="pre">read_msgpack</span></code></a>（path_or_buf [，encoding，iterator]）</span></td>
<td><span class="yiyi-st" id="yiyi-1117">从指定的加载msgpack pandas对象</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="clipboard">
<h3><span class="yiyi-st" id="yiyi-1118">剪贴板</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1119"><a class="reference internal" href="generated/pandas.read_clipboard.html#pandas.read_clipboard" title="pandas.read_clipboard"><code class="xref py py-obj docutils literal"><span class="pre">read_clipboard</span></code></a>（\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1120">从剪贴板读取文本并传递给read_table。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="excel">
<h3><span class="yiyi-st" id="yiyi-1121">Excel</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1122"><a class="reference internal" href="generated/pandas.read_excel.html#pandas.read_excel" title="pandas.read_excel"><code class="xref py py-obj docutils literal"><span class="pre">read_excel</span></code></a>（io [，sheetname，headers，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1123">将Excel表读入pandas DataFrame</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1124"><a class="reference internal" href="generated/pandas.ExcelFile.parse.html#pandas.ExcelFile.parse" title="pandas.ExcelFile.parse"><code class="xref py py-obj docutils literal"><span class="pre">ExcelFile.parse</span></code></a>（[sheetname，header，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1125">将指定的工作表解析到DataFrame中</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="json">
<h3><span class="yiyi-st" id="yiyi-1126">JSON</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1127"><a class="reference internal" href="generated/pandas.read_json.html#pandas.read_json" title="pandas.read_json"><code class="xref py py-obj docutils literal"><span class="pre">read_json</span></code></a>（[path_or_buf，orient，typ，dtype，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1128">将JSON字符串转换为pandas对象</span></td>
</tr>
</tbody>
</table>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1129"><a class="reference internal" href="generated/pandas.io.json.json_normalize.html#pandas.io.json.json_normalize" title="pandas.io.json.json_normalize"><code class="xref py py-obj docutils literal"><span class="pre">json_normalize</span></code></a>（data [，record_path，meta，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1130">将规范化的半结构化JSON数据转换为平面表格</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="html">
<h3><span class="yiyi-st" id="yiyi-1131">HTML</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1132"><a class="reference internal" href="generated/pandas.read_html.html#pandas.read_html" title="pandas.read_html"><code class="xref py py-obj docutils literal"><span class="pre">read_html</span></code></a>（io [，match，flavor，header，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1133">将HTML表格读入<code class="docutils literal"><span class="pre">DataFrame</span></code>对象的<code class="docutils literal"><span class="pre">list</span></code>。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="hdfstore-pytables-hdf5">
<h3><span class="yiyi-st" id="yiyi-1134">HDFStore: PyTables (HDF5)</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1135"><a class="reference internal" href="generated/pandas.read_hdf.html#pandas.read_hdf" title="pandas.read_hdf"><code class="xref py py-obj docutils literal"><span class="pre">read_hdf</span></code></a>（path_or_buf [，key]）</span></td>
<td><span class="yiyi-st" id="yiyi-1136">从商店读取，如果我们打开它关闭它</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1137"><a class="reference internal" href="generated/pandas.HDFStore.put.html#pandas.HDFStore.put" title="pandas.HDFStore.put"><code class="xref py py-obj docutils literal"><span class="pre">HDFStore.put</span></code></a>（key，value [，format，append]）</span></td>
<td><span class="yiyi-st" id="yiyi-1138">将对象存储在HDFStore中</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1139"><a class="reference internal" href="generated/pandas.HDFStore.append.html#pandas.HDFStore.append" title="pandas.HDFStore.append"><code class="xref py py-obj docutils literal"><span class="pre">HDFStore.append</span></code></a>（key，value [，format，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1140">附加到文件中的表。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1141"><a class="reference internal" href="generated/pandas.HDFStore.get.html#pandas.HDFStore.get" title="pandas.HDFStore.get"><code class="xref py py-obj docutils literal"><span class="pre">HDFStore.get</span></code></a>（key）</span></td>
<td><span class="yiyi-st" id="yiyi-1142">检索存储在文件中的pandas对象</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1143"><a class="reference internal" href="generated/pandas.HDFStore.select.html#pandas.HDFStore.select" title="pandas.HDFStore.select"><code class="xref py py-obj docutils literal"><span class="pre">HDFStore.select</span></code></a>（键[，其中，start，stop，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1144">检索存储在文件中的pandas对象，可选地基于where</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="sas">
<h3><span class="yiyi-st" id="yiyi-1145">SAS</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1146"><a class="reference internal" href="generated/pandas.read_sas.html#pandas.read_sas" title="pandas.read_sas"><code class="xref py py-obj docutils literal"><span class="pre">read_sas</span></code></a>（filepath_or_buffer [，format，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1147">读取以XPORT或SAS7BDAT格式文件存储的SAS文件。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="sql">
<h3><span class="yiyi-st" id="yiyi-1148">SQL</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1149"><a class="reference internal" href="generated/pandas.read_sql_table.html#pandas.read_sql_table" title="pandas.read_sql_table"><code class="xref py py-obj docutils literal"><span class="pre">read_sql_table</span></code></a>（table_name，con [，schema，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1150">将SQL数据库表读入DataFrame。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1151"><a class="reference internal" href="generated/pandas.read_sql_query.html#pandas.read_sql_query" title="pandas.read_sql_query"><code class="xref py py-obj docutils literal"><span class="pre">read_sql_query</span></code></a>（sql，con [，index_col，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1152">将SQL查询读入DataFrame。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1153"><a class="reference internal" href="generated/pandas.read_sql.html#pandas.read_sql" title="pandas.read_sql"><code class="xref py py-obj docutils literal"><span class="pre">read_sql</span></code></a>（sql，con [，index_col，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1154">将SQL查询或数据库表读入DataFrame。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="google-bigquery">
<h3><span class="yiyi-st" id="yiyi-1155">Google BigQuery</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1156"><a class="reference internal" href="generated/pandas.io.gbq.read_gbq.html#pandas.io.gbq.read_gbq" title="pandas.io.gbq.read_gbq"><code class="xref py py-obj docutils literal"><span class="pre">read_gbq</span></code></a>（query [，project_id，index_col，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1157">从Google BigQuery载入数据。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1158"><a class="reference internal" href="generated/pandas.io.gbq.to_gbq.html#pandas.io.gbq.to_gbq" title="pandas.io.gbq.to_gbq"><code class="xref py py-obj docutils literal"><span class="pre">to_gbq</span></code></a>（dataframe，destination_table，project_id）</span></td>
<td><span class="yiyi-st" id="yiyi-1159">将DataFrame写入Google BigQuery表格。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="stata">
<h3><span class="yiyi-st" id="yiyi-1160">STATA</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1161"><a class="reference internal" href="generated/pandas.read_stata.html#pandas.read_stata" title="pandas.read_stata"><code class="xref py py-obj docutils literal"><span class="pre">read_stata</span></code></a>（filepath_or_buffer [，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1162">将Stata文件读入DataFrame</span></td>
</tr>
</tbody>
</table>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1163"><a class="reference internal" href="generated/pandas.io.stata.StataReader.data.html#pandas.io.stata.StataReader.data" title="pandas.io.stata.StataReader.data"><code class="xref py py-obj docutils literal"><span class="pre">StataReader.data</span></code></a>（\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1164">DEPRECATED：从Stata文件读取观察结果，将它们转换为数据帧</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1165"><a class="reference internal" href="generated/pandas.io.stata.StataReader.data_label.html#pandas.io.stata.StataReader.data_label" title="pandas.io.stata.StataReader.data_label"><code class="xref py py-obj docutils literal"><span class="pre">StataReader.data_label</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1166">返回Stata文件的数据标签</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1167"><a class="reference internal" href="generated/pandas.io.stata.StataReader.value_labels.html#pandas.io.stata.StataReader.value_labels" title="pandas.io.stata.StataReader.value_labels"><code class="xref py py-obj docutils literal"><span class="pre">StataReader.value_labels</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1168">返回一个dict，关联每个变量名称一个dict，关联</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1169"><a class="reference internal" href="generated/pandas.io.stata.StataReader.variable_labels.html#pandas.io.stata.StataReader.variable_labels" title="pandas.io.stata.StataReader.variable_labels"><code class="xref py py-obj docutils literal"><span class="pre">StataReader.variable_labels</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1170">返回变量标签作为dict，关联每个变量名</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1171"><a class="reference internal" href="generated/pandas.io.stata.StataWriter.write_file.html#pandas.io.stata.StataWriter.write_file" title="pandas.io.stata.StataWriter.write_file"><code class="xref py py-obj docutils literal"><span class="pre">StataWriter.write_file</span></code></a>()</span></td>
<td></td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section" id="general-functions">
<h2><span class="yiyi-st" id="yiyi-1172">一般函数</span></h2>
<div class="section" id="data-manipulations">
<h3><span class="yiyi-st" id="yiyi-1173">数据操作</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1174"><a class="reference internal" href="generated/pandas.melt.html#pandas.melt" title="pandas.melt"><code class="xref py py-obj docutils literal"><span class="pre">melt</span></code></a>（frame [，id_vars，value_vars，var_name，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1175">将DataFrame从宽格式“不透明”为长格式，可选择离开</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1176"><a class="reference internal" href="generated/pandas.pivot.html#pandas.pivot" title="pandas.pivot"><code class="xref py py-obj docutils literal"><span class="pre">pivot</span></code></a>（索引，列，值）</span></td>
<td><span class="yiyi-st" id="yiyi-1177">基于此DataFrame的3列生成&apos;pivot&apos;表。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1178"><a class="reference internal" href="generated/pandas.pivot_table.html#pandas.pivot_table" title="pandas.pivot_table"><code class="xref py py-obj docutils literal"><span class="pre">pivot_table</span></code></a>（data [，values，index，columns，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1179">创建一个电子表格样式的数据透视表作为DataFrame。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1180"><a class="reference internal" href="generated/pandas.crosstab.html#pandas.crosstab" title="pandas.crosstab"><code class="xref py py-obj docutils literal"><span class="pre">crosstab</span></code></a>（索引，列[，values，rownames，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1181">计算两个（或更多）因子的简单交叉列表。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1182"><a class="reference internal" href="generated/pandas.cut.html#pandas.cut" title="pandas.cut"><code class="xref py py-obj docutils literal"><span class="pre">cut</span></code></a>（x，bins [，right，labels，retbins，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1183"><cite>x</cite>的每个值所属的半开箱的返回索引。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1184"><a class="reference internal" href="generated/pandas.qcut.html#pandas.qcut" title="pandas.qcut"><code class="xref py py-obj docutils literal"><span class="pre">qcut</span></code></a>（x，q [，labels，retbins，precision]）</span></td>
<td><span class="yiyi-st" id="yiyi-1185">基于分位数的离散化函数。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1186"><a class="reference internal" href="generated/pandas.merge.html#pandas.merge" title="pandas.merge"><code class="xref py py-obj docutils literal"><span class="pre">merge</span></code></a>（left，right [，how，on，left_on，...]</span></td>
<td><span class="yiyi-st" id="yiyi-1187">通过按列或索引执行数据库样式的连接操作来合并DataFrame对象。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1188"><a class="reference internal" href="generated/pandas.merge_ordered.html#pandas.merge_ordered" title="pandas.merge_ordered"><code class="xref py py-obj docutils literal"><span class="pre">merge_ordered</span></code></a>（left，right [，on，left_on，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1189">执行与为时序数据等有序数据设计的可选填充/插值合并。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1190"><a class="reference internal" href="generated/pandas.merge_asof.html#pandas.merge_asof" title="pandas.merge_asof"><code class="xref py py-obj docutils literal"><span class="pre">merge_asof</span></code></a>（left，right [，on，left_on，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1191">执行asof合并。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1192"><a class="reference internal" href="generated/pandas.concat.html#pandas.concat" title="pandas.concat"><code class="xref py py-obj docutils literal"><span class="pre">concat</span></code></a>（objs [，axis，join，join_axes，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1193">沿着特定轴连接pandas对象，沿着其他轴连接可选的设置逻辑。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1194"><a class="reference internal" href="generated/pandas.get_dummies.html#pandas.get_dummies" title="pandas.get_dummies"><code class="xref py py-obj docutils literal"><span class="pre">get_dummies</span></code></a>（data [，prefix，prefix_sep，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1195">将分类变量转换为虚拟/指示符变量</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1196"><a class="reference internal" href="generated/pandas.factorize.html#pandas.factorize" title="pandas.factorize"><code class="xref py py-obj docutils literal"><span class="pre">factorize</span></code></a>（values [，sort，order，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1197">将输入值编码为枚举类型或类别变量</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="top-level-missing-data">
<h3><span class="yiyi-st" id="yiyi-1198">顶级缺失数据</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1199"><a class="reference internal" href="generated/pandas.isnull.html#pandas.isnull" title="pandas.isnull"><code class="xref py py-obj docutils literal"><span class="pre">isnull</span></code></a>（obj）</span></td>
<td><span class="yiyi-st" id="yiyi-1200">检测缺失值（数值数组中的NaN，对象数组中的无/ NaN）</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1201"><a class="reference internal" href="generated/pandas.notnull.html#pandas.notnull" title="pandas.notnull"><code class="xref py py-obj docutils literal"><span class="pre">notnull</span></code></a>（obj）</span></td>
<td><span class="yiyi-st" id="yiyi-1202">替换适用于对象数组的numpy.isfinite / -numpy.isnan。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="top-level-conversions">
<h3><span class="yiyi-st" id="yiyi-1203">顶级转换</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1204"><a class="reference internal" href="generated/pandas.to_numeric.html#pandas.to_numeric" title="pandas.to_numeric"><code class="xref py py-obj docutils literal"><span class="pre">to_numeric</span></code></a>（arg [，errors，downcast]）</span></td>
<td><span class="yiyi-st" id="yiyi-1205">将参数转换为数字类型。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="top-level-dealing-with-datetimelike">
<h3><span class="yiyi-st" id="yiyi-1206">顶级处理datetimelike </span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1207"><a class="reference internal" href="generated/pandas.to_datetime.html#pandas.to_datetime" title="pandas.to_datetime"><code class="xref py py-obj docutils literal"><span class="pre">to_datetime</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1208">将参数转换为datetime。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1209"><a class="reference internal" href="generated/pandas.to_timedelta.html#pandas.to_timedelta" title="pandas.to_timedelta"><code class="xref py py-obj docutils literal"><span class="pre">to_timedelta</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1210">将参数转换为timedelta</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1211"><a class="reference internal" href="generated/pandas.date_range.html#pandas.date_range" title="pandas.date_range"><code class="xref py py-obj docutils literal"><span class="pre">date_range</span></code></a>（[start，end，periods，freq，tz，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1212">返回固定频率日期时间索引，将日（日历）作为默认值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1213"><a class="reference internal" href="generated/pandas.bdate_range.html#pandas.bdate_range" title="pandas.bdate_range"><code class="xref py py-obj docutils literal"><span class="pre">bdate_range</span></code></a>（[start，end，periods，freq，tz，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1214">返回固定频率datetime索引，以工作日为默认值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1215"><a class="reference internal" href="generated/pandas.period_range.html#pandas.period_range" title="pandas.period_range"><code class="xref py py-obj docutils literal"><span class="pre">period_range</span></code></a>（[start，end，periods，freq，name]）</span></td>
<td><span class="yiyi-st" id="yiyi-1216">返回固定频率日期时间索引，将日（日历）作为默认值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1217"><a class="reference internal" href="generated/pandas.timedelta_range.html#pandas.timedelta_range" title="pandas.timedelta_range"><code class="xref py py-obj docutils literal"><span class="pre">timedelta_range</span></code></a>（[start，end，periods，freq，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1218">返回固定频率timedelta索引，以天为默认值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1219"><a class="reference internal" href="generated/pandas.infer_freq.html#pandas.infer_freq" title="pandas.infer_freq"><code class="xref py py-obj docutils literal"><span class="pre">infer_freq</span></code></a>（index [，warn]）</span></td>
<td><span class="yiyi-st" id="yiyi-1220">给定输入索引，推断最可能的频率。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="top-level-evaluation">
<h3><span class="yiyi-st" id="yiyi-1221">顶级评估</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1222"><a class="reference internal" href="generated/pandas.eval.html#pandas.eval" title="pandas.eval"><code class="xref py py-obj docutils literal"><span class="pre">eval</span></code></a>（expr [，parser，engine，truediv，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1223">使用各种后端将Python表达式评估为字符串。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="testing">
<h3><span class="yiyi-st" id="yiyi-1224">测试</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1225"><a class="reference internal" href="generated/pandas.test.html#pandas.test" title="pandas.test"><code class="xref py py-obj docutils literal"><span class="pre">test</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1226">使用鼻子运行模块的测试。</span></td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section" id="series">
<span id="api-series"></span><h2><span class="yiyi-st" id="yiyi-1227">系列</span></h2>
<div class="section" id="constructor">
<h3><span class="yiyi-st" id="yiyi-1228">构造</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1229"><a class="reference internal" href="generated/pandas.Series.html#pandas.Series" title="pandas.Series"><code class="xref py py-obj docutils literal"><span class="pre">Series</span></code></a>（[data，index，dtype，name，copy，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1230">带轴标签的一维参考线（包括时间序列）。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="attributes">
<h3><span class="yiyi-st" id="yiyi-1231">属性</span></h3>
<dl class="docutils">
<dt><span class="yiyi-st" id="yiyi-1232"><strong>轴</strong></span></dt>
<dd><ul class="first last simple">
<li><span class="yiyi-st" id="yiyi-1233"><strong>索引</strong>：轴标签</span></li>
</ul>
</dd>
</dl>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1234"><a class="reference internal" href="generated/pandas.Series.values.html#pandas.Series.values" title="pandas.Series.values"><code class="xref py py-obj docutils literal"><span class="pre">Series.values</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1235">返回系列为ndarray或ndarray样</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1236"><a class="reference internal" href="generated/pandas.Series.dtype.html#pandas.Series.dtype" title="pandas.Series.dtype"><code class="xref py py-obj docutils literal"><span class="pre">Series.dtype</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1237">返回底层数据的dtype对象</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1238"><a class="reference internal" href="generated/pandas.Series.ftype.html#pandas.Series.ftype" title="pandas.Series.ftype"><code class="xref py py-obj docutils literal"><span class="pre">Series.ftype</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1239">返回如果数据稀疏|密集</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1240"><a class="reference internal" href="generated/pandas.Series.shape.html#pandas.Series.shape" title="pandas.Series.shape"><code class="xref py py-obj docutils literal"><span class="pre">Series.shape</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1241">返回基础数据的形状的元组</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1242"><a class="reference internal" href="generated/pandas.Series.nbytes.html#pandas.Series.nbytes" title="pandas.Series.nbytes"><code class="xref py py-obj docutils literal"><span class="pre">Series.nbytes</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1243">返回底层数据中的字节数</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1244"><a class="reference internal" href="generated/pandas.Series.ndim.html#pandas.Series.ndim" title="pandas.Series.ndim"><code class="xref py py-obj docutils literal"><span class="pre">Series.ndim</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1245">返回底层数据的维数，</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1246"><a class="reference internal" href="generated/pandas.Series.size.html#pandas.Series.size" title="pandas.Series.size"><code class="xref py py-obj docutils literal"><span class="pre">Series.size</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1247">返回底层数据中的元素数量</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1248"><a class="reference internal" href="generated/pandas.Series.strides.html#pandas.Series.strides" title="pandas.Series.strides"><code class="xref py py-obj docutils literal"><span class="pre">Series.strides</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1249">返回基础数据的步幅</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1250"><a class="reference internal" href="generated/pandas.Series.itemsize.html#pandas.Series.itemsize" title="pandas.Series.itemsize"><code class="xref py py-obj docutils literal"><span class="pre">Series.itemsize</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1251">返回底层数据项的dtype的大小</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1252"><a class="reference internal" href="generated/pandas.Series.base.html#pandas.Series.base" title="pandas.Series.base"><code class="xref py py-obj docutils literal"><span class="pre">Series.base</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1253">如果基础数据的内存是，则返回基础对象</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1254"><a class="reference internal" href="generated/pandas.Series.T.html#pandas.Series.T" title="pandas.Series.T"><code class="xref py py-obj docutils literal"><span class="pre">Series.T</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1255">返回转置，这是通过定义self</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1256"><a class="reference internal" href="generated/pandas.Series.memory_usage.html#pandas.Series.memory_usage" title="pandas.Series.memory_usage"><code class="xref py py-obj docutils literal"><span class="pre">Series.memory_usage</span></code></a>（[index，deep]）</span></td>
<td><span class="yiyi-st" id="yiyi-1257">系列的内存使用情况</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="conversion">
<h3><span class="yiyi-st" id="yiyi-1258">转换</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1259"><a class="reference internal" href="generated/pandas.Series.astype.html#pandas.Series.astype" title="pandas.Series.astype"><code class="xref py py-obj docutils literal"><span class="pre">Series.astype</span></code></a>（dtype [，copy，raise_on_error]）</span></td>
<td><span class="yiyi-st" id="yiyi-1260">投射对象以输入numpy.dtype</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1261"><a class="reference internal" href="generated/pandas.Series.copy.html#pandas.Series.copy" title="pandas.Series.copy"><code class="xref py py-obj docutils literal"><span class="pre">Series.copy</span></code></a>（[deep]）</span></td>
<td><span class="yiyi-st" id="yiyi-1262">复制此对象数据。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1263"><a class="reference internal" href="generated/pandas.Series.isnull.html#pandas.Series.isnull" title="pandas.Series.isnull"><code class="xref py py-obj docutils literal"><span class="pre">Series.isnull</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1264">返回一个布尔大小相同的对象，指示值是否为null。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1265"><a class="reference internal" href="generated/pandas.Series.notnull.html#pandas.Series.notnull" title="pandas.Series.notnull"><code class="xref py py-obj docutils literal"><span class="pre">Series.notnull</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1266">返回一个布尔大小相同的对象，指示这些值是否为空。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="indexing-iteration">
<h3><span class="yiyi-st" id="yiyi-1267">索引，迭代</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1268"><a class="reference internal" href="generated/pandas.Series.get.html#pandas.Series.get" title="pandas.Series.get"><code class="xref py py-obj docutils literal"><span class="pre">Series.get</span></code></a>（key [，default]）</span></td>
<td><span class="yiyi-st" id="yiyi-1269">从给定键的对象获取项目（DataFrame列，面板切片等</span><span class="yiyi-st" id="yiyi-1270">）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1271"><a class="reference internal" href="generated/pandas.Series.at.html#pandas.Series.at" title="pandas.Series.at"><code class="xref py py-obj docutils literal"><span class="pre">Series.at</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1272">基于快速标签的标量访问器</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1273"><a class="reference internal" href="generated/pandas.Series.iat.html#pandas.Series.iat" title="pandas.Series.iat"><code class="xref py py-obj docutils literal"><span class="pre">Series.iat</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1274">快速整数位置标量存取器。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1275"><a class="reference internal" href="generated/pandas.Series.ix.html#pandas.Series.ix" title="pandas.Series.ix"><code class="xref py py-obj docutils literal"><span class="pre">Series.ix</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1276">主要是基于标签位置的索引器，具有整数位置后备。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1277"><a class="reference internal" href="generated/pandas.Series.loc.html#pandas.Series.loc" title="pandas.Series.loc"><code class="xref py py-obj docutils literal"><span class="pre">Series.loc</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1278">纯标签位置索引器，用于按标签选择。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1279"><a class="reference internal" href="generated/pandas.Series.iloc.html#pandas.Series.iloc" title="pandas.Series.iloc"><code class="xref py py-obj docutils literal"><span class="pre">Series.iloc</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1280">纯粹基于整数位置的索引，用于按位置选择。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1281"><a class="reference internal" href="generated/pandas.Series.__iter__.html#pandas.Series.__iter__" title="pandas.Series.__iter__"><code class="xref py py-obj docutils literal"><span class="pre">Series.__iter__</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1282">提供对系列的值的迭代</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1283"><a class="reference internal" href="generated/pandas.Series.iteritems.html#pandas.Series.iteritems" title="pandas.Series.iteritems"><code class="xref py py-obj docutils literal"><span class="pre">Series.iteritems</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1284">Lazily迭代（索引，值）元组</span></td>
</tr>
</tbody>
</table>
<p><span class="yiyi-st" id="yiyi-1285">有关<code class="docutils literal"><span class="pre">.at</span></code>，<code class="docutils literal"><span class="pre">.iat</span></code>，<code class="docutils literal"><span class="pre">.ix</span></code>，<code class="docutils literal"><span class="pre">.loc</span></code>和<code class="docutils literal"><span class="pre">.iloc</span></code>，请参阅<a class="reference internal" href="indexing.html#indexing"><span class="std std-ref">indexing documentation</span></a>。</span></p>
</div>
<div class="section" id="binary-operator-functions">
<h3><span class="yiyi-st" id="yiyi-1286">二进制运算符函数</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1287"><a class="reference internal" href="generated/pandas.Series.add.html#pandas.Series.add" title="pandas.Series.add"><code class="xref py py-obj docutils literal"><span class="pre">Series.add</span></code></a>（其他[，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1288">添加系列和其他，元素方式（二元运算符<cite>add</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1289"><a class="reference internal" href="generated/pandas.Series.sub.html#pandas.Series.sub" title="pandas.Series.sub"><code class="xref py py-obj docutils literal"><span class="pre">Series.sub</span></code></a>（其他[，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1290">减法系数和其他，元素方式（二元运算符<cite>子</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1291"><a class="reference internal" href="generated/pandas.Series.mul.html#pandas.Series.mul" title="pandas.Series.mul"><code class="xref py py-obj docutils literal"><span class="pre">Series.mul</span></code></a>（其他[，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1292">系列和其他元素乘法（二元算符<cite>mul</cite>）的乘法。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1293"><a class="reference internal" href="generated/pandas.Series.div.html#pandas.Series.div" title="pandas.Series.div"><code class="xref py py-obj docutils literal"><span class="pre">Series.div</span></code></a>（其他[，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1294">浮点除法的系列和其他，元素（二进制运算符<cite>truediv</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1295"><a class="reference internal" href="generated/pandas.Series.truediv.html#pandas.Series.truediv" title="pandas.Series.truediv"><code class="xref py py-obj docutils literal"><span class="pre">Series.truediv</span></code></a>（other [，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1296">浮点除法的系列和其他，元素（二进制运算符<cite>truediv</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1297"><a class="reference internal" href="generated/pandas.Series.floordiv.html#pandas.Series.floordiv" title="pandas.Series.floordiv"><code class="xref py py-obj docutils literal"><span class="pre">Series.floordiv</span></code></a>（其他[，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1298">系列的整数除法和其他，元素方式（二元运算符<cite>floordiv</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1299"><a class="reference internal" href="generated/pandas.Series.mod.html#pandas.Series.mod" title="pandas.Series.mod"><code class="xref py py-obj docutils literal"><span class="pre">Series.mod</span></code></a>（其他[，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1300">系列模和其他，元素方式（二元运算符<cite>mod</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1301"><a class="reference internal" href="generated/pandas.Series.pow.html#pandas.Series.pow" title="pandas.Series.pow"><code class="xref py py-obj docutils literal"><span class="pre">Series.pow</span></code></a>（其他[，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1302">系数和其他元指数（二元运算符<cite>pow</cite>）的指数幂。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1303"><a class="reference internal" href="generated/pandas.Series.radd.html#pandas.Series.radd" title="pandas.Series.radd"><code class="xref py py-obj docutils literal"><span class="pre">Series.radd</span></code></a>（其他[，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1304">添加系列和其他，元素方式（二元算符<cite>radd</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1305"><a class="reference internal" href="generated/pandas.Series.rsub.html#pandas.Series.rsub" title="pandas.Series.rsub"><code class="xref py py-obj docutils literal"><span class="pre">Series.rsub</span></code></a>（其他[，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1306">减法系列和其他，元素方式（二元运算符<cite>rsub</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1307"><a class="reference internal" href="generated/pandas.Series.rmul.html#pandas.Series.rmul" title="pandas.Series.rmul"><code class="xref py py-obj docutils literal"><span class="pre">Series.rmul</span></code></a>（其他[，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1308">系列和其他元素乘法（二元算符<cite>rmul</cite>）的乘法。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1309"><a class="reference internal" href="generated/pandas.Series.rdiv.html#pandas.Series.rdiv" title="pandas.Series.rdiv"><code class="xref py py-obj docutils literal"><span class="pre">Series.rdiv</span></code></a>（其他[，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1310">浮点除法的系列和其他，元素（二进制运算符<cite>rtruediv</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1311"><a class="reference internal" href="generated/pandas.Series.rtruediv.html#pandas.Series.rtruediv" title="pandas.Series.rtruediv"><code class="xref py py-obj docutils literal"><span class="pre">Series.rtruediv</span></code></a>（other [，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1312">浮点除法的系列和其他，元素（二进制运算符<cite>rtruediv</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1313"><a class="reference internal" href="generated/pandas.Series.rfloordiv.html#pandas.Series.rfloordiv" title="pandas.Series.rfloordiv"><code class="xref py py-obj docutils literal"><span class="pre">Series.rfloordiv</span></code></a>（other [，level，fill_value，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1314">系列的整数除法和其他，元素方式（二元运算符<cite>rfloordiv</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1315"><a class="reference internal" href="generated/pandas.Series.rmod.html#pandas.Series.rmod" title="pandas.Series.rmod"><code class="xref py py-obj docutils literal"><span class="pre">Series.rmod</span></code></a>（其他[，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1316">系列模和其他，元素方式（二元算符<cite>rmod</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1317"><a class="reference internal" href="generated/pandas.Series.rpow.html#pandas.Series.rpow" title="pandas.Series.rpow"><code class="xref py py-obj docutils literal"><span class="pre">Series.rpow</span></code></a>（其他[，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1318">系列和其他元指数（二元运算符<cite>rpow</cite>）的指数幂。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1319"><a class="reference internal" href="generated/pandas.Series.combine.html#pandas.Series.combine" title="pandas.Series.combine"><code class="xref py py-obj docutils literal"><span class="pre">Series.combine</span></code></a>（other，func [，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-1320">对两个系列使用给定的函数执行元素二进制操作</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1321"><a class="reference internal" href="generated/pandas.Series.combine_first.html#pandas.Series.combine_first" title="pandas.Series.combine_first"><code class="xref py py-obj docutils literal"><span class="pre">Series.combine_first</span></code></a>（other）</span></td>
<td><span class="yiyi-st" id="yiyi-1322">组合系列值，首先选择调用系列的值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1323"><a class="reference internal" href="generated/pandas.Series.round.html#pandas.Series.round" title="pandas.Series.round"><code class="xref py py-obj docutils literal"><span class="pre">Series.round</span></code></a>（[小数]）</span></td>
<td><span class="yiyi-st" id="yiyi-1324">将系列中的每个值四舍五入为给定的小数位数。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1325"><a class="reference internal" href="generated/pandas.Series.lt.html#pandas.Series.lt" title="pandas.Series.lt"><code class="xref py py-obj docutils literal"><span class="pre">Series.lt</span></code></a>（其他[，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1326">小于系列和其他，元素方式（二元运算符<cite>lt</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1327"><a class="reference internal" href="generated/pandas.Series.gt.html#pandas.Series.gt" title="pandas.Series.gt"><code class="xref py py-obj docutils literal"><span class="pre">Series.gt</span></code></a>（其他[，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1328">大于系列和其他，元素方式（二元运算符<cite>gt</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1329"><a class="reference internal" href="generated/pandas.Series.le.html#pandas.Series.le" title="pandas.Series.le"><code class="xref py py-obj docutils literal"><span class="pre">Series.le</span></code></a>（其他[，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1330">小于或等于系列和其他，元素方式（二元运算符<cite>le</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1331"><a class="reference internal" href="generated/pandas.Series.ge.html#pandas.Series.ge" title="pandas.Series.ge"><code class="xref py py-obj docutils literal"><span class="pre">Series.ge</span></code></a>（其他[，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1332">大于或等于系列和其他，元素方式（二元运算符<cite>ge</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1333"><a class="reference internal" href="generated/pandas.Series.ne.html#pandas.Series.ne" title="pandas.Series.ne"><code class="xref py py-obj docutils literal"><span class="pre">Series.ne</span></code></a>（其他[，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1334">不等于系列和其他，元素方式（二元运算符<cite>ne</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1335"><a class="reference internal" href="generated/pandas.Series.eq.html#pandas.Series.eq" title="pandas.Series.eq"><code class="xref py py-obj docutils literal"><span class="pre">Series.eq</span></code></a>（other [，level，fill_value，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1336">等于系列和其他，元素方式（二元运算符<cite>eq</cite>）。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="function-application-groupby-window">
<h3><span class="yiyi-st" id="yiyi-1337">功能应用，GroupBy &amp; Window</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1338"><a class="reference internal" href="generated/pandas.Series.apply.html#pandas.Series.apply" title="pandas.Series.apply"><code class="xref py py-obj docutils literal"><span class="pre">Series.apply</span></code></a>（func [，convert_dtype，args]）</span></td>
<td><span class="yiyi-st" id="yiyi-1339">对Series的值调用函数。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1340"><a class="reference internal" href="generated/pandas.Series.map.html#pandas.Series.map" title="pandas.Series.map"><code class="xref py py-obj docutils literal"><span class="pre">Series.map</span></code></a>（arg [，na_action]）</span></td>
<td><span class="yiyi-st" id="yiyi-1341">使用输入对应关系（可以是</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1342"><a class="reference internal" href="generated/pandas.Series.groupby.html#pandas.Series.groupby" title="pandas.Series.groupby"><code class="xref py py-obj docutils literal"><span class="pre">Series.groupby</span></code></a>（[by，axis，level，as_index，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1343">使用mapper的组系列（dict或key函数，将给定函数应用于组，将结果返回为系列）或通过一系列列。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1344"><a class="reference internal" href="generated/pandas.Series.rolling.html#pandas.Series.rolling" title="pandas.Series.rolling"><code class="xref py py-obj docutils literal"><span class="pre">Series.rolling</span></code></a>（window [，min_periods，freq，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1345">提供滚动窗口计算。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1346"><a class="reference internal" href="generated/pandas.Series.expanding.html#pandas.Series.expanding" title="pandas.Series.expanding"><code class="xref py py-obj docutils literal"><span class="pre">Series.expanding</span></code></a>（[min_periods，freq，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1347">提供扩展转换。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1348"><a class="reference internal" href="generated/pandas.Series.ewm.html#pandas.Series.ewm" title="pandas.Series.ewm"><code class="xref py py-obj docutils literal"><span class="pre">Series.ewm</span></code></a>（[com，span，halflife，alpha，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1349">提供指数加权函数</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="computations-descriptive-stats">
<span id="api-series-stats"></span><h3><span class="yiyi-st" id="yiyi-1350">计算/描述性统计</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1351"><a class="reference internal" href="generated/pandas.Series.abs.html#pandas.Series.abs" title="pandas.Series.abs"><code class="xref py py-obj docutils literal"><span class="pre">Series.abs</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1352">返回具有绝对值的对象，仅适用于全部为数字的对象。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1353"><a class="reference internal" href="generated/pandas.Series.all.html#pandas.Series.all" title="pandas.Series.all"><code class="xref py py-obj docutils literal"><span class="pre">Series.all</span></code></a>（[axis，bool_only，skipna，level]）</span></td>
<td><span class="yiyi-st" id="yiyi-1354">返回所有元素是否超过请求的轴的True</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1355"><a class="reference internal" href="generated/pandas.Series.any.html#pandas.Series.any" title="pandas.Series.any"><code class="xref py py-obj docutils literal"><span class="pre">Series.any</span></code></a>（[axis，bool_only，skipna，level]）</span></td>
<td><span class="yiyi-st" id="yiyi-1356">返回任何元素是否超过请求的轴为True</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1357"><a class="reference internal" href="generated/pandas.Series.autocorr.html#pandas.Series.autocorr" title="pandas.Series.autocorr"><code class="xref py py-obj docutils literal"><span class="pre">Series.autocorr</span></code></a>（[lag]）</span></td>
<td><span class="yiyi-st" id="yiyi-1358">Lag-N自相关</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1359"><a class="reference internal" href="generated/pandas.Series.between.html#pandas.Series.between" title="pandas.Series.between"><code class="xref py py-obj docutils literal"><span class="pre">Series.between</span></code></a>（左，右[，含]）</span></td>
<td><span class="yiyi-st" id="yiyi-1360">返回boolean系列相当于left</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1361"><a class="reference internal" href="generated/pandas.Series.clip.html#pandas.Series.clip" title="pandas.Series.clip"><code class="xref py py-obj docutils literal"><span class="pre">Series.clip</span></code></a>（[下，上，轴]）</span></td>
<td><span class="yiyi-st" id="yiyi-1362">修整输入阈值处的值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1363"><a class="reference internal" href="generated/pandas.Series.clip_lower.html#pandas.Series.clip_lower" title="pandas.Series.clip_lower"><code class="xref py py-obj docutils literal"><span class="pre">Series.clip_lower</span></code></a>（threshold [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1364">返回具有低于给定值的值的输入的副本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1365"><a class="reference internal" href="generated/pandas.Series.clip_upper.html#pandas.Series.clip_upper" title="pandas.Series.clip_upper"><code class="xref py py-obj docutils literal"><span class="pre">Series.clip_upper</span></code></a>（threshold [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1366">返回具有高于给定值的值的输入的副本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1367"><a class="reference internal" href="generated/pandas.Series.corr.html#pandas.Series.corr" title="pandas.Series.corr"><code class="xref py py-obj docutils literal"><span class="pre">Series.corr</span></code></a>（other [，method，min_periods]）</span></td>
<td><span class="yiyi-st" id="yiyi-1368">与<cite>其他</cite>系列计算相关性，不包括缺少的值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1369"><a class="reference internal" href="generated/pandas.Series.count.html#pandas.Series.count" title="pandas.Series.count"><code class="xref py py-obj docutils literal"><span class="pre">Series.count</span></code></a>（[level]）</span></td>
<td><span class="yiyi-st" id="yiyi-1370">返回系列中非NA /零值观察值的数量</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1371"><a class="reference internal" href="generated/pandas.Series.cov.html#pandas.Series.cov" title="pandas.Series.cov"><code class="xref py py-obj docutils literal"><span class="pre">Series.cov</span></code></a>（其他[，min_periods]）</span></td>
<td><span class="yiyi-st" id="yiyi-1372">计算与系列的协方差，不包括缺少的值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1373"><a class="reference internal" href="generated/pandas.Series.cummax.html#pandas.Series.cummax" title="pandas.Series.cummax"><code class="xref py py-obj docutils literal"><span class="pre">Series.cummax</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-1374">返回请求轴上的累积最大值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1375"><a class="reference internal" href="generated/pandas.Series.cummin.html#pandas.Series.cummin" title="pandas.Series.cummin"><code class="xref py py-obj docutils literal"><span class="pre">Series.cummin</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-1376">返回所请求轴上的累积最小值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1377"><a class="reference internal" href="generated/pandas.Series.cumprod.html#pandas.Series.cumprod" title="pandas.Series.cumprod"><code class="xref py py-obj docutils literal"><span class="pre">Series.cumprod</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-1378">通过请求轴返回累积乘积。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1379"><a class="reference internal" href="generated/pandas.Series.cumsum.html#pandas.Series.cumsum" title="pandas.Series.cumsum"><code class="xref py py-obj docutils literal"><span class="pre">Series.cumsum</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-1380">通过请求轴返回累积和。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1381"><a class="reference internal" href="generated/pandas.Series.describe.html#pandas.Series.describe" title="pandas.Series.describe"><code class="xref py py-obj docutils literal"><span class="pre">Series.describe</span></code></a>（[percentiles，include，exclude]）</span></td>
<td><span class="yiyi-st" id="yiyi-1382">生成各种汇总统计，不包括NaN值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1383"><a class="reference internal" href="generated/pandas.Series.diff.html#pandas.Series.diff" title="pandas.Series.diff"><code class="xref py py-obj docutils literal"><span class="pre">Series.diff</span></code></a>（[periods]）</span></td>
<td><span class="yiyi-st" id="yiyi-1384">对象的第一离散差异</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1385"><a class="reference internal" href="generated/pandas.Series.factorize.html#pandas.Series.factorize" title="pandas.Series.factorize"><code class="xref py py-obj docutils literal"><span class="pre">Series.factorize</span></code></a>（[sort，na_sentinel]）</span></td>
<td><span class="yiyi-st" id="yiyi-1386">将对象编码为枚举类型或类别变量</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1387"><a class="reference internal" href="generated/pandas.Series.kurt.html#pandas.Series.kurt" title="pandas.Series.kurt"><code class="xref py py-obj docutils literal"><span class="pre">Series.kurt</span></code></a>（[axis，skipna，level，numeric_only]）</span></td>
<td><span class="yiyi-st" id="yiyi-1388">使用Fisher的峰度定义（kurtosis of normal == 0.0）返回无偏的峰度超过请求的轴。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1389"><a class="reference internal" href="generated/pandas.Series.mad.html#pandas.Series.mad" title="pandas.Series.mad"><code class="xref py py-obj docutils literal"><span class="pre">Series.mad</span></code></a>（[axis，skipna，level]）</span></td>
<td><span class="yiyi-st" id="yiyi-1390">返回请求轴的值的平均绝对偏差</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1391"><a class="reference internal" href="generated/pandas.Series.max.html#pandas.Series.max" title="pandas.Series.max"><code class="xref py py-obj docutils literal"><span class="pre">Series.max</span></code></a>（[axis，skipna，level，numeric_only]）</span></td>
<td><span class="yiyi-st" id="yiyi-1392">此方法返回对象中值的最大值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1393"><a class="reference internal" href="generated/pandas.Series.mean.html#pandas.Series.mean" title="pandas.Series.mean"><code class="xref py py-obj docutils literal"><span class="pre">Series.mean</span></code></a>（[axis，skipna，level，numeric_only]）</span></td>
<td><span class="yiyi-st" id="yiyi-1394">返回请求轴的值的平均值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1395"><a class="reference internal" href="generated/pandas.Series.median.html#pandas.Series.median" title="pandas.Series.median"><code class="xref py py-obj docutils literal"><span class="pre">Series.median</span></code></a>（[axis，skipna，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1396">返回请求轴的值的中值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1397"><a class="reference internal" href="generated/pandas.Series.min.html#pandas.Series.min" title="pandas.Series.min"><code class="xref py py-obj docutils literal"><span class="pre">Series.min</span></code></a>（[axis，skipna，level，numeric_only]）</span></td>
<td><span class="yiyi-st" id="yiyi-1398">此方法返回对象中值的最小值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1399"><a class="reference internal" href="generated/pandas.Series.mode.html#pandas.Series.mode" title="pandas.Series.mode"><code class="xref py py-obj docutils literal"><span class="pre">Series.mode</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1400">返回数据集的模式。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1401"><a class="reference internal" href="generated/pandas.Series.nlargest.html#pandas.Series.nlargest" title="pandas.Series.nlargest"><code class="xref py py-obj docutils literal"><span class="pre">Series.nlargest</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1402">返回最大的<cite>n</cite>元素。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1403"><a class="reference internal" href="generated/pandas.Series.nsmallest.html#pandas.Series.nsmallest" title="pandas.Series.nsmallest"><code class="xref py py-obj docutils literal"><span class="pre">Series.nsmallest</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1404">返回最小的<cite>n</cite>元素。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1405"><a class="reference internal" href="generated/pandas.Series.pct_change.html#pandas.Series.pct_change" title="pandas.Series.pct_change"><code class="xref py py-obj docutils literal"><span class="pre">Series.pct_change</span></code></a>（[periods，fill_method，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1406">给定周期数的百分比变化。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1407"><a class="reference internal" href="generated/pandas.Series.prod.html#pandas.Series.prod" title="pandas.Series.prod"><code class="xref py py-obj docutils literal"><span class="pre">Series.prod</span></code></a>（[axis，skipna，level，numeric_only]）</span></td>
<td><span class="yiyi-st" id="yiyi-1408">返回请求轴的值的乘积</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1409"><a class="reference internal" href="generated/pandas.Series.quantile.html#pandas.Series.quantile" title="pandas.Series.quantile"><code class="xref py py-obj docutils literal"><span class="pre">Series.quantile</span></code></a>（[q，interpolation]）</span></td>
<td><span class="yiyi-st" id="yiyi-1410">返回给定分位数的值，即一个数字。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1411"><a class="reference internal" href="generated/pandas.Series.rank.html#pandas.Series.rank" title="pandas.Series.rank"><code class="xref py py-obj docutils literal"><span class="pre">Series.rank</span></code></a>（[axis，method，numeric_only，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1412">沿轴计算数值数据（1到n）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1413"><a class="reference internal" href="generated/pandas.Series.sem.html#pandas.Series.sem" title="pandas.Series.sem"><code class="xref py py-obj docutils literal"><span class="pre">Series.sem</span></code></a>（[axis，skipna，level，ddof，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1414">返回所要求轴的平均值的无偏差标准误差。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1415"><a class="reference internal" href="generated/pandas.Series.skew.html#pandas.Series.skew" title="pandas.Series.skew"><code class="xref py py-obj docutils literal"><span class="pre">Series.skew</span></code></a>([axis, skipna, level, numeric_only])</span></td>
<td><span class="yiyi-st" id="yiyi-1416">返回所请求轴的无偏斜</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1417"><a class="reference internal" href="generated/pandas.Series.std.html#pandas.Series.std" title="pandas.Series.std"><code class="xref py py-obj docutils literal"><span class="pre">Series.std</span></code></a>（[axis，skipna，level，ddof，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1418">返回样品标准偏差超过请求的轴。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1419"><a class="reference internal" href="generated/pandas.Series.sum.html#pandas.Series.sum" title="pandas.Series.sum"><code class="xref py py-obj docutils literal"><span class="pre">Series.sum</span></code></a>（[axis，skipna，level，numeric_only]）</span></td>
<td><span class="yiyi-st" id="yiyi-1420">返回请求轴的值的总和</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1421"><a class="reference internal" href="generated/pandas.Series.var.html#pandas.Series.var" title="pandas.Series.var"><code class="xref py py-obj docutils literal"><span class="pre">Series.var</span></code></a>（[axis，skipna，level，ddof，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1422">返回与请求轴无关的方差。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1423"><a class="reference internal" href="generated/pandas.Series.unique.html#pandas.Series.unique" title="pandas.Series.unique"><code class="xref py py-obj docutils literal"><span class="pre">Series.unique</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1424">返回对象中的唯一值的np.ndarray。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1425"><a class="reference internal" href="generated/pandas.Series.nunique.html#pandas.Series.nunique" title="pandas.Series.nunique"><code class="xref py py-obj docutils literal"><span class="pre">Series.nunique</span></code></a>（[dropna]）</span></td>
<td><span class="yiyi-st" id="yiyi-1426">返回对象中唯一元素的数量。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1427"><a class="reference internal" href="generated/pandas.Series.is_unique.html#pandas.Series.is_unique" title="pandas.Series.is_unique"><code class="xref py py-obj docutils literal"><span class="pre">Series.is_unique</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1428">如果对象中的值是唯一的，则返回布尔值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1429"><a class="reference internal" href="generated/pandas.Series.is_monotonic.html#pandas.Series.is_monotonic" title="pandas.Series.is_monotonic"><code class="xref py py-obj docutils literal"><span class="pre">Series.is_monotonic</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1430">如果对象中的值为，则返回布尔值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1431"><a class="reference internal" href="generated/pandas.Series.is_monotonic_increasing.html#pandas.Series.is_monotonic_increasing" title="pandas.Series.is_monotonic_increasing"><code class="xref py py-obj docutils literal"><span class="pre">Series.is_monotonic_increasing</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1432">如果对象中的值为，则返回布尔值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1433"><a class="reference internal" href="generated/pandas.Series.is_monotonic_decreasing.html#pandas.Series.is_monotonic_decreasing" title="pandas.Series.is_monotonic_decreasing"><code class="xref py py-obj docutils literal"><span class="pre">Series.is_monotonic_decreasing</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1434">如果对象中的值为，则返回布尔值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1435"><a class="reference internal" href="generated/pandas.Series.value_counts.html#pandas.Series.value_counts" title="pandas.Series.value_counts"><code class="xref py py-obj docutils literal"><span class="pre">Series.value_counts</span></code></a>（[normalize，sort，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1436">返回包含唯一值计数的对象。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="reindexing-selection-label-manipulation">
<h3><span class="yiyi-st" id="yiyi-1437">重新索引/选择/标签操作</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1438"><a class="reference internal" href="generated/pandas.Series.align.html#pandas.Series.align" title="pandas.Series.align"><code class="xref py py-obj docutils literal"><span class="pre">Series.align</span></code></a>（其他[，join，axis，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1439">将它们的轴上的两个对象与</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1440"><a class="reference internal" href="generated/pandas.Series.drop.html#pandas.Series.drop" title="pandas.Series.drop"><code class="xref py py-obj docutils literal"><span class="pre">Series.drop</span></code></a>（标签[，axis，level，inplace，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1441">返回请求轴中标签已删除的新对象。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1442"><a class="reference internal" href="generated/pandas.Series.drop_duplicates.html#pandas.Series.drop_duplicates" title="pandas.Series.drop_duplicates"><code class="xref py py-obj docutils literal"><span class="pre">Series.drop_duplicates</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1443">删除重复值的返回系列</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1444"><a class="reference internal" href="generated/pandas.Series.duplicated.html#pandas.Series.duplicated" title="pandas.Series.duplicated"><code class="xref py py-obj docutils literal"><span class="pre">Series.duplicated</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1445">返回boolean表示重复值的系列</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1446"><a class="reference internal" href="generated/pandas.Series.equals.html#pandas.Series.equals" title="pandas.Series.equals"><code class="xref py py-obj docutils literal"><span class="pre">Series.equals</span></code></a>（other）</span></td>
<td><span class="yiyi-st" id="yiyi-1447">确定两个NDFrame对象是否包含相同的元素。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1448"><a class="reference internal" href="generated/pandas.Series.first.html#pandas.Series.first" title="pandas.Series.first"><code class="xref py py-obj docutils literal"><span class="pre">Series.first</span></code></a>（offset）</span></td>
<td><span class="yiyi-st" id="yiyi-1449">用于基于日期偏移对时间序列数据的初始时间进行子集化的便利方法。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1450"><a class="reference internal" href="generated/pandas.Series.head.html#pandas.Series.head" title="pandas.Series.head"><code class="xref py py-obj docutils literal"><span class="pre">Series.head</span></code></a>（[n]）</span></td>
<td><span class="yiyi-st" id="yiyi-1451">返回前n行</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1452"><a class="reference internal" href="generated/pandas.Series.idxmax.html#pandas.Series.idxmax" title="pandas.Series.idxmax"><code class="xref py py-obj docutils literal"><span class="pre">Series.idxmax</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-1453">首次出现最大值的索引。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1454"><a class="reference internal" href="generated/pandas.Series.idxmin.html#pandas.Series.idxmin" title="pandas.Series.idxmin"><code class="xref py py-obj docutils literal"><span class="pre">Series.idxmin</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-1455">首次出现最小值的索引。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1456"><a class="reference internal" href="generated/pandas.Series.isin.html#pandas.Series.isin" title="pandas.Series.isin"><code class="xref py py-obj docutils literal"><span class="pre">Series.isin</span></code></a>（values）</span></td>
<td><span class="yiyi-st" id="yiyi-1457">返回布尔<a class="reference internal" href="generated/pandas.Series.html#pandas.Series" title="pandas.Series"><code class="xref py py-class docutils literal"><span class="pre">Series</span></code></a>，显示<a class="reference internal" href="generated/pandas.Series.html#pandas.Series" title="pandas.Series"><code class="xref py py-class docutils literal"><span class="pre">Series</span></code></a>中的每个元素是否完全包含在传递的<code class="docutils literal"><span class="pre">values</span></code>序列中。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1458"><a class="reference internal" href="generated/pandas.Series.last.html#pandas.Series.last" title="pandas.Series.last"><code class="xref py py-obj docutils literal"><span class="pre">Series.last</span></code></a>（offset）</span></td>
<td><span class="yiyi-st" id="yiyi-1459">基于日期偏移对时间序列数据的最终周期子集化的便利方法。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1460"><a class="reference internal" href="generated/pandas.Series.reindex.html#pandas.Series.reindex" title="pandas.Series.reindex"><code class="xref py py-obj docutils literal"><span class="pre">Series.reindex</span></code></a>（[index]）</span></td>
<td><span class="yiyi-st" id="yiyi-1461">使用可选填充逻辑将系列更新为新索引，将NA / NaN放在前一个索引中没有值的位置。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1462"><a class="reference internal" href="generated/pandas.Series.reindex_like.html#pandas.Series.reindex_like" title="pandas.Series.reindex_like"><code class="xref py py-obj docutils literal"><span class="pre">Series.reindex_like</span></code></a>（other [，method，copy，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1463">将具有匹配索引的对象返回给我自己。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1464"><a class="reference internal" href="generated/pandas.Series.rename.html#pandas.Series.rename" title="pandas.Series.rename"><code class="xref py py-obj docutils literal"><span class="pre">Series.rename</span></code></a>（[index]）</span></td>
<td><span class="yiyi-st" id="yiyi-1465">改变轴输入功能。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1466"><a class="reference internal" href="generated/pandas.Series.rename_axis.html#pandas.Series.rename_axis" title="pandas.Series.rename_axis"><code class="xref py py-obj docutils literal"><span class="pre">Series.rename_axis</span></code></a>（mapper [，axis，copy，inplace]）</span></td>
<td><span class="yiyi-st" id="yiyi-1467">使用输入函数或函数修改索引和/或列。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1468"><a class="reference internal" href="generated/pandas.Series.reset_index.html#pandas.Series.reset_index" title="pandas.Series.reset_index"><code class="xref py py-obj docutils literal"><span class="pre">Series.reset_index</span></code></a>（[level，drop，name，inplace]）</span></td>
<td><span class="yiyi-st" id="yiyi-1469">类似于<a class="reference internal" href="generated/pandas.DataFrame.reset_index.html#pandas.DataFrame.reset_index" title="pandas.DataFrame.reset_index"><code class="xref py py-meth docutils literal"><span class="pre">pandas.DataFrame.reset_index()</span></code></a>函数，请参见docstring。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1470"><a class="reference internal" href="generated/pandas.Series.sample.html#pandas.Series.sample" title="pandas.Series.sample"><code class="xref py py-obj docutils literal"><span class="pre">Series.sample</span></code></a>（[n，frac，replace，weights，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1471">从对象的轴返回项目的随机样本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1472"><a class="reference internal" href="generated/pandas.Series.select.html#pandas.Series.select" title="pandas.Series.select"><code class="xref py py-obj docutils literal"><span class="pre">Series.select</span></code></a>（crit [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1473">返回与轴标签匹配条件相对应的数据</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1474"><a class="reference internal" href="generated/pandas.Series.take.html#pandas.Series.take" title="pandas.Series.take"><code class="xref py py-obj docutils literal"><span class="pre">Series.take</span></code></a>（indices [，axis，convert，is_copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-1475">return对应于请求的索引</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1476"><a class="reference internal" href="generated/pandas.Series.tail.html#pandas.Series.tail" title="pandas.Series.tail"><code class="xref py py-obj docutils literal"><span class="pre">Series.tail</span></code></a>（[n]）</span></td>
<td><span class="yiyi-st" id="yiyi-1477">返回最后n行</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1478"><a class="reference internal" href="generated/pandas.Series.truncate.html#pandas.Series.truncate" title="pandas.Series.truncate"><code class="xref py py-obj docutils literal"><span class="pre">Series.truncate</span></code></a>（[before，after，axis，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-1479">在某个特定索引值之前和/或之后截断排序的NDFrame。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1480"><a class="reference internal" href="generated/pandas.Series.where.html#pandas.Series.where" title="pandas.Series.where"><code class="xref py py-obj docutils literal"><span class="pre">Series.where</span></code></a>（cond [，other，inplace，axis，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1481">返回一个与self相同形状的对象，其对应的条目来自self，其中cond为True，否则为其他对象。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1482"><a class="reference internal" href="generated/pandas.Series.mask.html#pandas.Series.mask" title="pandas.Series.mask"><code class="xref py py-obj docutils literal"><span class="pre">Series.mask</span></code></a>（cond [，other，inplace，axis，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1483">返回一个与self相同形状的对象，并且其对应的条目来自self，其中cond是False，否则是来自其他。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="missing-data-handling">
<h3><span class="yiyi-st" id="yiyi-1484">缺少数据处理</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1485"><a class="reference internal" href="generated/pandas.Series.dropna.html#pandas.Series.dropna" title="pandas.Series.dropna"><code class="xref py py-obj docutils literal"><span class="pre">Series.dropna</span></code></a>（[axis，inplace]）</span></td>
<td><span class="yiyi-st" id="yiyi-1486">返回无null值的系列</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1487"><a class="reference internal" href="generated/pandas.Series.fillna.html#pandas.Series.fillna" title="pandas.Series.fillna"><code class="xref py py-obj docutils literal"><span class="pre">Series.fillna</span></code></a>（[value，method，axis，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1488">使用指定的方法填充NA / NaN值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1489"><a class="reference internal" href="generated/pandas.Series.interpolate.html#pandas.Series.interpolate" title="pandas.Series.interpolate"><code class="xref py py-obj docutils literal"><span class="pre">Series.interpolate</span></code></a>（[method，axis，limit，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1490">根据不同的方法内插值。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="reshaping-sorting">
<h3><span class="yiyi-st" id="yiyi-1491">重新整形，排序</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1492"><a class="reference internal" href="generated/pandas.Series.argsort.html#pandas.Series.argsort" title="pandas.Series.argsort"><code class="xref py py-obj docutils literal"><span class="pre">Series.argsort</span></code></a>（[axis，kind，order]）</span></td>
<td><span class="yiyi-st" id="yiyi-1493">覆盖ndarray.argsort。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1494"><a class="reference internal" href="generated/pandas.Series.reorder_levels.html#pandas.Series.reorder_levels" title="pandas.Series.reorder_levels"><code class="xref py py-obj docutils literal"><span class="pre">Series.reorder_levels</span></code></a>（order）</span></td>
<td><span class="yiyi-st" id="yiyi-1495">使用输入顺序重新排列索引级别。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1496"><a class="reference internal" href="generated/pandas.Series.sort_values.html#pandas.Series.sort_values" title="pandas.Series.sort_values"><code class="xref py py-obj docutils literal"><span class="pre">Series.sort_values</span></code></a>（[axis，ascending，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1497">按任一轴的值排序</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1498"><a class="reference internal" href="generated/pandas.Series.sort_index.html#pandas.Series.sort_index" title="pandas.Series.sort_index"><code class="xref py py-obj docutils literal"><span class="pre">Series.sort_index</span></code></a>（[axis，level，ascending，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1499">按标签（沿轴）对对象排序</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1500"><a class="reference internal" href="generated/pandas.Series.sortlevel.html#pandas.Series.sortlevel" title="pandas.Series.sortlevel"><code class="xref py py-obj docutils literal"><span class="pre">Series.sortlevel</span></code></a>（[level，ascending，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1501">按所选级别对MultiIndex进行排序。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1502"><a class="reference internal" href="generated/pandas.Series.swaplevel.html#pandas.Series.swaplevel" title="pandas.Series.swaplevel"><code class="xref py py-obj docutils literal"><span class="pre">Series.swaplevel</span></code></a>（[i，j，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-1503">在MultiIndex中交换级别i和j</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1504"><a class="reference internal" href="generated/pandas.Series.unstack.html#pandas.Series.unstack" title="pandas.Series.unstack"><code class="xref py py-obj docutils literal"><span class="pre">Series.unstack</span></code></a>（[level，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-1505">Unstack，a.k.a.</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1506"><a class="reference internal" href="generated/pandas.Series.searchsorted.html#pandas.Series.searchsorted" title="pandas.Series.searchsorted"><code class="xref py py-obj docutils literal"><span class="pre">Series.searchsorted</span></code></a>（v [，side，sorter]）</span></td>
<td><span class="yiyi-st" id="yiyi-1507">查找要插入元素以维持顺序的索引。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="combining-joining-merging">
<h3><span class="yiyi-st" id="yiyi-1508">组合/加入/合并</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1509"><a class="reference internal" href="generated/pandas.Series.append.html#pandas.Series.append" title="pandas.Series.append"><code class="xref py py-obj docutils literal"><span class="pre">Series.append</span></code></a>（to_append [，ignore_index，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1510">串联两个或更多系列。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1511"><a class="reference internal" href="generated/pandas.Series.replace.html#pandas.Series.replace" title="pandas.Series.replace"><code class="xref py py-obj docutils literal"><span class="pre">Series.replace</span></code></a>（[to_replace，value，inplace，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1512">将&apos;to_replace&apos;中给出的值替换为&apos;value&apos;。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1513"><a class="reference internal" href="generated/pandas.Series.update.html#pandas.Series.update" title="pandas.Series.update"><code class="xref py py-obj docutils literal"><span class="pre">Series.update</span></code></a>（other）</span></td>
<td><span class="yiyi-st" id="yiyi-1514">使用通过的系列中的非NA值修改系列。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="time-series-related">
<h3><span class="yiyi-st" id="yiyi-1515">时间序列相关的</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1516"><a class="reference internal" href="generated/pandas.Series.asfreq.html#pandas.Series.asfreq" title="pandas.Series.asfreq"><code class="xref py py-obj docutils literal"><span class="pre">Series.asfreq</span></code></a>（freq [，method，how，normalize]）</span></td>
<td><span class="yiyi-st" id="yiyi-1517">将TimeSeries转换为指定的频率。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1518"><a class="reference internal" href="generated/pandas.Series.asof.html#pandas.Series.asof" title="pandas.Series.asof"><code class="xref py py-obj docutils literal"><span class="pre">Series.asof</span></code></a>（其中[，subset]）</span></td>
<td><span class="yiyi-st" id="yiyi-1519">最后一行没有任何NaN被采取（或最后一行没有</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1520"><a class="reference internal" href="generated/pandas.Series.shift.html#pandas.Series.shift" title="pandas.Series.shift"><code class="xref py py-obj docutils literal"><span class="pre">Series.shift</span></code></a>（[periods，freq，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1521">使用可选的时间频率按期望的周期数切换索引</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1522"><a class="reference internal" href="generated/pandas.Series.first_valid_index.html#pandas.Series.first_valid_index" title="pandas.Series.first_valid_index"><code class="xref py py-obj docutils literal"><span class="pre">Series.first_valid_index</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1523">返回第一个非NA /空值的标签</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1524"><a class="reference internal" href="generated/pandas.Series.last_valid_index.html#pandas.Series.last_valid_index" title="pandas.Series.last_valid_index"><code class="xref py py-obj docutils literal"><span class="pre">Series.last_valid_index</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1525">返回最后一个非NA /空值的标签</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1526"><a class="reference internal" href="generated/pandas.Series.resample.html#pandas.Series.resample" title="pandas.Series.resample"><code class="xref py py-obj docutils literal"><span class="pre">Series.resample</span></code></a>（rule [，how，axis，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1527">时间序列的频率转换和重采样的方便方法。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1528"><a class="reference internal" href="generated/pandas.Series.tz_convert.html#pandas.Series.tz_convert" title="pandas.Series.tz_convert"><code class="xref py py-obj docutils literal"><span class="pre">Series.tz_convert</span></code></a>（tz [，axis，level，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-1529">将tz感知轴转换为目标时区。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1530"><a class="reference internal" href="generated/pandas.Series.tz_localize.html#pandas.Series.tz_localize" title="pandas.Series.tz_localize"><code class="xref py py-obj docutils literal"><span class="pre">Series.tz_localize</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1531">将tz-naive TimeSeries本地化为目标时区。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="datetimelike-properties">
<h3><span class="yiyi-st" id="yiyi-1532">Datetimelike属性</span></h3>
<p><span class="yiyi-st" id="yiyi-1533"><code class="docutils literal"><span class="pre">Series.dt</span></code>可用于以datetimelike访问系列的值，并返回多个属性。</span><span class="yiyi-st" id="yiyi-1534">这些可以像<code class="docutils literal"><span class="pre">Series.dt.&lt;property&gt;</span></code>一样访问。</span></p>
<p><span class="yiyi-st" id="yiyi-1535"><strong>日期时间属性</strong></span></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1536"><a class="reference internal" href="generated/pandas.Series.dt.date.html#pandas.Series.dt.date" title="pandas.Series.dt.date"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.date</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1537">返回numpy数组的python datetime.date对象（即，没有时区信息的时间戳的日期部分）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1538"><a class="reference internal" href="generated/pandas.Series.dt.time.html#pandas.Series.dt.time" title="pandas.Series.dt.time"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.time</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1539">返回datetime.time的numpy数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1540"><a class="reference internal" href="generated/pandas.Series.dt.year.html#pandas.Series.dt.year" title="pandas.Series.dt.year"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.year</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1541">datetime的年份</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1542"><a class="reference internal" href="generated/pandas.Series.dt.month.html#pandas.Series.dt.month" title="pandas.Series.dt.month"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.month</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1543">月份为1月= 1月，12月= 12月</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1544"><a class="reference internal" href="generated/pandas.Series.dt.day.html#pandas.Series.dt.day" title="pandas.Series.dt.day"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.day</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1545">datetime的日期</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1546"><a class="reference internal" href="generated/pandas.Series.dt.hour.html#pandas.Series.dt.hour" title="pandas.Series.dt.hour"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.hour</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1547">datetime的小时数</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1548"><a class="reference internal" href="generated/pandas.Series.dt.minute.html#pandas.Series.dt.minute" title="pandas.Series.dt.minute"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.minute</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1549">datetime的分钟</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1550"><a class="reference internal" href="generated/pandas.Series.dt.second.html#pandas.Series.dt.second" title="pandas.Series.dt.second"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.second</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1551">datetime的秒数</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1552"><a class="reference internal" href="generated/pandas.Series.dt.microsecond.html#pandas.Series.dt.microsecond" title="pandas.Series.dt.microsecond"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.microsecond</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1553">datetime的微秒</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1554"><a class="reference internal" href="generated/pandas.Series.dt.nanosecond.html#pandas.Series.dt.nanosecond" title="pandas.Series.dt.nanosecond"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.nanosecond</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1555">datetime的纳秒</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1556"><a class="reference internal" href="generated/pandas.Series.dt.week.html#pandas.Series.dt.week" title="pandas.Series.dt.week"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.week</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1557">一年的周数</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1558"><a class="reference internal" href="generated/pandas.Series.dt.weekofyear.html#pandas.Series.dt.weekofyear" title="pandas.Series.dt.weekofyear"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.weekofyear</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1559">一年的周数</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1560"><a class="reference internal" href="generated/pandas.Series.dt.dayofweek.html#pandas.Series.dt.dayofweek" title="pandas.Series.dt.dayofweek"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.dayofweek</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1561">一周中的星期几，星期一= 0，星期六= 6</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1562"><a class="reference internal" href="generated/pandas.Series.dt.weekday.html#pandas.Series.dt.weekday" title="pandas.Series.dt.weekday"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.weekday</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1563">一周中的星期几，星期一= 0，星期六= 6</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1564"><a class="reference internal" href="generated/pandas.Series.dt.weekday_name.html#pandas.Series.dt.weekday_name" title="pandas.Series.dt.weekday_name"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.weekday_name</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1565">一周中的日期名称（例如：星期五）</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1566"><a class="reference internal" href="generated/pandas.Series.dt.dayofyear.html#pandas.Series.dt.dayofyear" title="pandas.Series.dt.dayofyear"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.dayofyear</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1567">一年的序数日</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1568"><a class="reference internal" href="generated/pandas.Series.dt.quarter.html#pandas.Series.dt.quarter" title="pandas.Series.dt.quarter"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.quarter</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1569">日期的四分之一</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1570"><a class="reference internal" href="generated/pandas.Series.dt.is_month_start.html#pandas.Series.dt.is_month_start" title="pandas.Series.dt.is_month_start"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.is_month_start</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1571">逻辑指示是否每月的第一天（由频率定义）</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1572"><a class="reference internal" href="generated/pandas.Series.dt.is_month_end.html#pandas.Series.dt.is_month_end" title="pandas.Series.dt.is_month_end"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.is_month_end</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1573">逻辑指示是否每月的最后一天（由频率定义）</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1574"><a class="reference internal" href="generated/pandas.Series.dt.is_quarter_start.html#pandas.Series.dt.is_quarter_start" title="pandas.Series.dt.is_quarter_start"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.is_quarter_start</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1575">逻辑指示季度的第一天（由频率定义）</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1576"><a class="reference internal" href="generated/pandas.Series.dt.is_quarter_end.html#pandas.Series.dt.is_quarter_end" title="pandas.Series.dt.is_quarter_end"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.is_quarter_end</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1577">逻辑指示季度的最后一天（由频率定义）</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1578"><a class="reference internal" href="generated/pandas.Series.dt.is_year_start.html#pandas.Series.dt.is_year_start" title="pandas.Series.dt.is_year_start"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.is_year_start</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1579">逻辑指示一年中的第一天（由频率定义）</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1580"><a class="reference internal" href="generated/pandas.Series.dt.is_year_end.html#pandas.Series.dt.is_year_end" title="pandas.Series.dt.is_year_end"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.is_year_end</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1581">逻辑指示一年中的最后一天（由频率定义）</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1582"><a class="reference internal" href="generated/pandas.Series.dt.is_leap_year.html#pandas.Series.dt.is_leap_year" title="pandas.Series.dt.is_leap_year"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.is_leap_year</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1583">逻辑指示日期是否属于闰年</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1584"><a class="reference internal" href="generated/pandas.Series.dt.daysinmonth.html#pandas.Series.dt.daysinmonth" title="pandas.Series.dt.daysinmonth"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.daysinmonth</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1585">每月的天数</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1586"><a class="reference internal" href="generated/pandas.Series.dt.days_in_month.html#pandas.Series.dt.days_in_month" title="pandas.Series.dt.days_in_month"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.days_in_month</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1587">每月的天数</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1588"><a class="reference internal" href="generated/pandas.Series.dt.tz.html#pandas.Series.dt.tz" title="pandas.Series.dt.tz"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.tz</span></code></a></span></td>
<td></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1589"><a class="reference internal" href="generated/pandas.Series.dt.freq.html#pandas.Series.dt.freq" title="pandas.Series.dt.freq"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.freq</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1590">获取/设置索引的频率</span></td>
</tr>
</tbody>
</table>
<p><span class="yiyi-st" id="yiyi-1591"><strong>日期时间方法</strong></span></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1592"><a class="reference internal" href="generated/pandas.Series.dt.to_period.html#pandas.Series.dt.to_period" title="pandas.Series.dt.to_period"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.to_period</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1593">以特定频率投射到PeriodIndex</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1594"><a class="reference internal" href="generated/pandas.Series.dt.to_pydatetime.html#pandas.Series.dt.to_pydatetime" title="pandas.Series.dt.to_pydatetime"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.to_pydatetime</span></code></a>()</span></td>
<td></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1595"><a class="reference internal" href="generated/pandas.Series.dt.tz_localize.html#pandas.Series.dt.tz_localize" title="pandas.Series.dt.tz_localize"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.tz_localize</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1596">将tz-naive DatetimeIndex本地化到给定时区（使用</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1597"><a class="reference internal" href="generated/pandas.Series.dt.tz_convert.html#pandas.Series.dt.tz_convert" title="pandas.Series.dt.tz_convert"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.tz_convert</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1598">将tz感知DatetimeIndex从一个时区转换到另一个（使用</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1599"><a class="reference internal" href="generated/pandas.Series.dt.normalize.html#pandas.Series.dt.normalize" title="pandas.Series.dt.normalize"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.normalize</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1600">将DatetimeIndex与时间返回到午夜。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1601"><a class="reference internal" href="generated/pandas.Series.dt.strftime.html#pandas.Series.dt.strftime" title="pandas.Series.dt.strftime"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.strftime</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1602">返回由date_format指定的格式化字符串数组，该数组支持与python标准库相同的字符串格式。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1603"><a class="reference internal" href="generated/pandas.Series.dt.round.html#pandas.Series.dt.round" title="pandas.Series.dt.round"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.round</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1604">将索引循环到指定的频率</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1605"><a class="reference internal" href="generated/pandas.Series.dt.floor.html#pandas.Series.dt.floor" title="pandas.Series.dt.floor"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.floor</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1606">将索引落到指定的频率</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1607"><a class="reference internal" href="generated/pandas.Series.dt.ceil.html#pandas.Series.dt.ceil" title="pandas.Series.dt.ceil"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.ceil</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1608">ceil索引到指定的频率</span></td>
</tr>
</tbody>
</table>
<p><span class="yiyi-st" id="yiyi-1609"><strong>Timedelta属性</strong></span></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1610"><a class="reference internal" href="generated/pandas.Series.dt.days.html#pandas.Series.dt.days" title="pandas.Series.dt.days"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.days</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1611">每个元素的天数。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1612"><a class="reference internal" href="generated/pandas.Series.dt.seconds.html#pandas.Series.dt.seconds" title="pandas.Series.dt.seconds"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.seconds</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1613">每个元素的秒数（&gt; = 0和小于1天）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1614"><a class="reference internal" href="generated/pandas.Series.dt.microseconds.html#pandas.Series.dt.microseconds" title="pandas.Series.dt.microseconds"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.microseconds</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1615">每个元素的微秒数（&gt; = 0和小于1秒）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1616"><a class="reference internal" href="generated/pandas.Series.dt.nanoseconds.html#pandas.Series.dt.nanoseconds" title="pandas.Series.dt.nanoseconds"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.nanoseconds</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1617">每个元素的纳秒数（&gt; = 0和小于1微秒）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1618"><a class="reference internal" href="generated/pandas.Series.dt.components.html#pandas.Series.dt.components" title="pandas.Series.dt.components"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.components</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1619">返回Timedeltas的组件（天，小时，分钟，秒，毫秒，微秒，纳秒）的数据帧。</span></td>
</tr>
</tbody>
</table>
<p><span class="yiyi-st" id="yiyi-1620"><strong>Timedelta方法</strong></span></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1621"><a class="reference internal" href="generated/pandas.Series.dt.to_pytimedelta.html#pandas.Series.dt.to_pytimedelta" title="pandas.Series.dt.to_pytimedelta"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.to_pytimedelta</span></code></a>()</span></td>
<td></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1622"><a class="reference internal" href="generated/pandas.Series.dt.total_seconds.html#pandas.Series.dt.total_seconds" title="pandas.Series.dt.total_seconds"><code class="xref py py-obj docutils literal"><span class="pre">Series.dt.total_seconds</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1623">每个元素的总持续时间，单位为秒。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="string-handling">
<h3><span class="yiyi-st" id="yiyi-1624">字符串处理</span></h3>
<p><span class="yiyi-st" id="yiyi-1625"><code class="docutils literal"><span class="pre">Series.str</span></code>可用于以字符串的形式访问系列的值，并对其应用多种方法。</span><span class="yiyi-st" id="yiyi-1626">这些可以像<code class="docutils literal"><span class="pre">Series.str.&lt;function/property&gt;</span></code>一样访问。</span></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1627"><a class="reference internal" href="generated/pandas.Series.str.capitalize.html#pandas.Series.str.capitalize" title="pandas.Series.str.capitalize"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.capitalize</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1628">转换要大写的系列/索引中的字符串。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1629"><a class="reference internal" href="generated/pandas.Series.str.cat.html#pandas.Series.str.cat" title="pandas.Series.str.cat"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.cat</span></code></a>（[others，sep，na_rep]）</span></td>
<td><span class="yiyi-st" id="yiyi-1630">None</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1631"><a class="reference internal" href="generated/pandas.Series.str.center.html#pandas.Series.str.center" title="pandas.Series.str.center"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.center</span></code></a>（width [，fillchar]）</span></td>
<td><span class="yiyi-st" id="yiyi-1632">使用附加字符填充系列/索引中字符串的左侧和右侧。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1633"><a class="reference internal" href="generated/pandas.Series.str.contains.html#pandas.Series.str.contains" title="pandas.Series.str.contains"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.contains</span></code></a>（pat [，case，flags，na，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1634">返回boolean Series / <code class="docutils literal"><span class="pre">array</span></code>是否在Series / Index中的每个字符串中包含给定pattern / regex。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1635"><a class="reference internal" href="generated/pandas.Series.str.count.html#pandas.Series.str.count" title="pandas.Series.str.count"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.count</span></code></a>（pat [，flags]）</span></td>
<td><span class="yiyi-st" id="yiyi-1636">计算系列/索引的每个字符串中模式的出现次数。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1637"><a class="reference internal" href="generated/pandas.Series.str.decode.html#pandas.Series.str.decode" title="pandas.Series.str.decode"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.decode</span></code></a>（encoding [，errors]）</span></td>
<td><span class="yiyi-st" id="yiyi-1638">使用指定的编码对Series / Index中的字符串进行解码。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1639"><a class="reference internal" href="generated/pandas.Series.str.encode.html#pandas.Series.str.encode" title="pandas.Series.str.encode"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.encode</span></code></a>（encoding [，errors]）</span></td>
<td><span class="yiyi-st" id="yiyi-1640">使用指定的编码对Series / Index中的字符串进行编码。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1641"><a class="reference internal" href="generated/pandas.Series.str.endswith.html#pandas.Series.str.endswith" title="pandas.Series.str.endswith"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.endswith</span></code></a>（pat [，na]）</span></td>
<td><span class="yiyi-st" id="yiyi-1642">返回boolean表示系列/索引中的每个字符串是否以传递模式结束的系列。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1643"><a class="reference internal" href="generated/pandas.Series.str.extract.html#pandas.Series.str.extract" title="pandas.Series.str.extract"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.extract</span></code></a>（pat [，flags，expand]）</span></td>
<td><span class="yiyi-st" id="yiyi-1644">对于系列中的每个主题字符串，从正则表达式pat的第一个匹配中提取组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1645"><a class="reference internal" href="generated/pandas.Series.str.extractall.html#pandas.Series.str.extractall" title="pandas.Series.str.extractall"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.extractall</span></code></a>（pat [，flags]）</span></td>
<td><span class="yiyi-st" id="yiyi-1646">对于系列中的每个主题字符串，从正则表达式pat的所有匹配中提取组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1647"><a class="reference internal" href="generated/pandas.Series.str.find.html#pandas.Series.str.find" title="pandas.Series.str.find"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.find</span></code></a>（sub [，start，end]）</span></td>
<td><span class="yiyi-st" id="yiyi-1648">返回系列/索引中每个字符串中的最低索引，其中子字符串完全包含在[start：end]之间。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1649"><a class="reference internal" href="generated/pandas.Series.str.findall.html#pandas.Series.str.findall" title="pandas.Series.str.findall"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.findall</span></code></a>（pat [，flags]）</span></td>
<td><span class="yiyi-st" id="yiyi-1650">在Series / Index中查找所有出现的模式或正则表达式。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1651"><a class="reference internal" href="generated/pandas.Series.str.get.html#pandas.Series.str.get" title="pandas.Series.str.get"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.get</span></code></a>（i）</span></td>
<td><span class="yiyi-st" id="yiyi-1652">从系列/索引中的每个元素中的列表，元组或字符串中提取元素。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1653"><a class="reference internal" href="generated/pandas.Series.str.index.html#pandas.Series.str.index" title="pandas.Series.str.index"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.index</span></code></a>（sub [，start，end]）</span></td>
<td><span class="yiyi-st" id="yiyi-1654">返回每个字符串中的最低索引，其中子字符串完全包含在[start：end]之间。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1655"><a class="reference internal" href="generated/pandas.Series.str.join.html#pandas.Series.str.join" title="pandas.Series.str.join"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.join</span></code></a>（sep）</span></td>
<td><span class="yiyi-st" id="yiyi-1656">加入列表作为元素在Series / Index中包含传递的分隔符。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1657"><a class="reference internal" href="generated/pandas.Series.str.len.html#pandas.Series.str.len" title="pandas.Series.str.len"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.len</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1658">计算系列/索引中每个字符串的长度。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1659"><a class="reference internal" href="generated/pandas.Series.str.ljust.html#pandas.Series.str.ljust" title="pandas.Series.str.ljust"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.ljust</span></code></a>（width [，fillchar]）</span></td>
<td><span class="yiyi-st" id="yiyi-1660">使用附加字符填充系列/索引中字符串的右侧。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1661"><a class="reference internal" href="generated/pandas.Series.str.lower.html#pandas.Series.str.lower" title="pandas.Series.str.lower"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.lower</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1662">将Series / Index中的字符串转换为小写。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1663"><a class="reference internal" href="generated/pandas.Series.str.lstrip.html#pandas.Series.str.lstrip" title="pandas.Series.str.lstrip"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.lstrip</span></code></a>（[to_strip]）</span></td>
<td><span class="yiyi-st" id="yiyi-1664">从左侧的系列/索引中的每个字符串剥除空格（包括换行符）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1665"><a class="reference internal" href="generated/pandas.Series.str.match.html#pandas.Series.str.match" title="pandas.Series.str.match"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.match</span></code></a>（pat [，case，flags，na，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1666">不推荐：使用传递的正则表达式在Series / Index中的每个字符串中查找组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1667"><a class="reference internal" href="generated/pandas.Series.str.normalize.html#pandas.Series.str.normalize" title="pandas.Series.str.normalize"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.normalize</span></code></a>（form）</span></td>
<td><span class="yiyi-st" id="yiyi-1668">返回系列/索引中的字符串的Unicode正常形式。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1669"><a class="reference internal" href="generated/pandas.Series.str.pad.html#pandas.Series.str.pad" title="pandas.Series.str.pad"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.pad</span></code></a>（width [，side，fillchar]）</span></td>
<td><span class="yiyi-st" id="yiyi-1670">在系列/索引中的填充字符串，在指定的一侧有一个附加字符。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1671"><a class="reference internal" href="generated/pandas.Series.str.partition.html#pandas.Series.str.partition" title="pandas.Series.str.partition"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.partition</span></code></a>（[pat，expand]）</span></td>
<td><span class="yiyi-st" id="yiyi-1672">拆分第一次出现<cite>sep</cite>时的字符串，并返回包含分隔符之前的零件，分隔符本身和分隔符后面的零件的3个元素。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1673"><a class="reference internal" href="generated/pandas.Series.str.repeat.html#pandas.Series.str.repeat" title="pandas.Series.str.repeat"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.repeat</span></code></a>（重复）</span></td>
<td><span class="yiyi-st" id="yiyi-1674">按照指定的次数复制系列/索引中的每个字符串。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1675"><a class="reference internal" href="generated/pandas.Series.str.replace.html#pandas.Series.str.replace" title="pandas.Series.str.replace"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.replace</span></code></a>（pat，repl [，n，case，flags]）</span></td>
<td><span class="yiyi-st" id="yiyi-1676">用一些其他字符串替换Series / Index中的pattern / regex的出现。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1677"><a class="reference internal" href="generated/pandas.Series.str.rfind.html#pandas.Series.str.rfind" title="pandas.Series.str.rfind"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.rfind</span></code></a>（sub [，start，end]）</span></td>
<td><span class="yiyi-st" id="yiyi-1678">返回系列/索引中每个字符串中的最高索引，其中子字符串完全包含在[start：end]之间。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1679"><a class="reference internal" href="generated/pandas.Series.str.rindex.html#pandas.Series.str.rindex" title="pandas.Series.str.rindex"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.rindex</span></code></a>（sub [，start，end]）</span></td>
<td><span class="yiyi-st" id="yiyi-1680">返回每个字符串中的最高索引，其中子字符串完全包含在[start：end]之间。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1681"><a class="reference internal" href="generated/pandas.Series.str.rjust.html#pandas.Series.str.rjust" title="pandas.Series.str.rjust"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.rjust</span></code></a>（width [，fillchar]）</span></td>
<td><span class="yiyi-st" id="yiyi-1682">使用附加字符填充系列/索引中字符串的左侧。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1683"><a class="reference internal" href="generated/pandas.Series.str.rpartition.html#pandas.Series.str.rpartition" title="pandas.Series.str.rpartition"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.rpartition</span></code></a>（[pat，expand]）</span></td>
<td><span class="yiyi-st" id="yiyi-1684">拆分最后一次出现<cite>sep</cite>时的字符串，并返回包含分隔符之前的零件，分隔符本身和分隔符后面的零件的3个元素。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1685"><a class="reference internal" href="generated/pandas.Series.str.rstrip.html#pandas.Series.str.rstrip" title="pandas.Series.str.rstrip"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.rstrip</span></code></a>（[to_strip]）</span></td>
<td><span class="yiyi-st" id="yiyi-1686">从右侧系列/索引中的每个字符串剥除空格（包括换行符）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1687"><a class="reference internal" href="generated/pandas.Series.str.slice.html#pandas.Series.str.slice" title="pandas.Series.str.slice"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.slice</span></code></a>（[start，stop，step]）</span></td>
<td><span class="yiyi-st" id="yiyi-1688">从Series / Index中的每个元素切割子串</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1689"><a class="reference internal" href="generated/pandas.Series.str.slice_replace.html#pandas.Series.str.slice_replace" title="pandas.Series.str.slice_replace"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.slice_replace</span></code></a>（[start，stop，repl]）</span></td>
<td><span class="yiyi-st" id="yiyi-1690">将Series / Index中的每个字符串的切片替换为另一个字符串。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1691"><a class="reference internal" href="generated/pandas.Series.str.split.html#pandas.Series.str.split" title="pandas.Series.str.split"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.split</span></code></a>（[pat，n，expand]）</span></td>
<td><span class="yiyi-st" id="yiyi-1692">按照给定模式拆分系列/索引中的每个字符串（a la re.split），传播NA值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1693"><a class="reference internal" href="generated/pandas.Series.str.rsplit.html#pandas.Series.str.rsplit" title="pandas.Series.str.rsplit"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.rsplit</span></code></a>（[pat，n，expand]）</span></td>
<td><span class="yiyi-st" id="yiyi-1694">使用给定的分隔符字符串将系列/索引中的每个字符串拆分，从字符串的结尾开始，并向前面进行。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1695"><a class="reference internal" href="generated/pandas.Series.str.startswith.html#pandas.Series.str.startswith" title="pandas.Series.str.startswith"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.startswith</span></code></a>（pat [，na]）</span></td>
<td><span class="yiyi-st" id="yiyi-1696">返回布尔系列/ <code class="docutils literal"><span class="pre">array</span></code>指示Series / Index中的每个字符串是否以传递模式开头。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1697"><a class="reference internal" href="generated/pandas.Series.str.strip.html#pandas.Series.str.strip" title="pandas.Series.str.strip"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.strip</span></code></a>（[to_strip]）</span></td>
<td><span class="yiyi-st" id="yiyi-1698">从左/右边的系列/索引中的每个字符串剥离空格（包括换行符）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1699"><a class="reference internal" href="generated/pandas.Series.str.swapcase.html#pandas.Series.str.swapcase" title="pandas.Series.str.swapcase"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.swapcase</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1700">转换要交换的系列/索引中的字符串。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1701"><a class="reference internal" href="generated/pandas.Series.str.title.html#pandas.Series.str.title" title="pandas.Series.str.title"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.title</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1702">将系列/索引中的字符串转换为titlecase。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1703"><a class="reference internal" href="generated/pandas.Series.str.translate.html#pandas.Series.str.translate" title="pandas.Series.str.translate"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.translate</span></code></a>（table [，deletechars]）</span></td>
<td><span class="yiyi-st" id="yiyi-1704">通过给定的映射表映射字符串中的所有字符。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1705"><a class="reference internal" href="generated/pandas.Series.str.upper.html#pandas.Series.str.upper" title="pandas.Series.str.upper"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.upper</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1706">将Series / Index中的字符串转换为大写。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1707"><a class="reference internal" href="generated/pandas.Series.str.wrap.html#pandas.Series.str.wrap" title="pandas.Series.str.wrap"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.wrap</span></code></a>（width，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1708">在要在长度小于给定宽度的段落中格式化的系列/索引中包装长字符串。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1709"><a class="reference internal" href="generated/pandas.Series.str.zfill.html#pandas.Series.str.zfill" title="pandas.Series.str.zfill"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.zfill</span></code></a>（width）</span></td>
<td><span class="yiyi-st" id="yiyi-1710">填充系列/索引中的字符串左侧为0。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1711"><a class="reference internal" href="generated/pandas.Series.str.isalnum.html#pandas.Series.str.isalnum" title="pandas.Series.str.isalnum"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.isalnum</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1712">检查系列/索引中每个字符串中的所有字符是否为字母数字。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1713"><a class="reference internal" href="generated/pandas.Series.str.isalpha.html#pandas.Series.str.isalpha" title="pandas.Series.str.isalpha"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.isalpha</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1714">检查系列/索引中每个字符串中的所有字符是否为字母。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1715"><a class="reference internal" href="generated/pandas.Series.str.isdigit.html#pandas.Series.str.isdigit" title="pandas.Series.str.isdigit"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.isdigit</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1716">检查系列/索引中每个字符串中的所有字符是否为数字。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1717"><a class="reference internal" href="generated/pandas.Series.str.isspace.html#pandas.Series.str.isspace" title="pandas.Series.str.isspace"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.isspace</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1718">检查Series / Index中每个字符串中的所有字符是否为空格。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1719"><a class="reference internal" href="generated/pandas.Series.str.islower.html#pandas.Series.str.islower" title="pandas.Series.str.islower"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.islower</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1720">检查系列/索引中每个字符串中的所有字符是否为小写。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1721"><a class="reference internal" href="generated/pandas.Series.str.isupper.html#pandas.Series.str.isupper" title="pandas.Series.str.isupper"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.isupper</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1722">检查系列/索引中每个字符串中的所有字符是否为大写。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1723"><a class="reference internal" href="generated/pandas.Series.str.istitle.html#pandas.Series.str.istitle" title="pandas.Series.str.istitle"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.istitle</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1724">检查系列/索引中每个字符串中的所有字符是否都是titlecase。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1725"><a class="reference internal" href="generated/pandas.Series.str.isnumeric.html#pandas.Series.str.isnumeric" title="pandas.Series.str.isnumeric"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.isnumeric</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1726">检查系列/索引中每个字符串中的所有字符是否都是数字。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1727"><a class="reference internal" href="generated/pandas.Series.str.isdecimal.html#pandas.Series.str.isdecimal" title="pandas.Series.str.isdecimal"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.isdecimal</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1728">检查系列/索引中每个字符串中的所有字符是否为十进制。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1729"><a class="reference internal" href="generated/pandas.Series.str.get_dummies.html#pandas.Series.str.get_dummies" title="pandas.Series.str.get_dummies"><code class="xref py py-obj docutils literal"><span class="pre">Series.str.get_dummies</span></code></a>（[sep]）</span></td>
<td><span class="yiyi-st" id="yiyi-1730">将系列中的每个字符串拆分为sep，并返回一个虚拟/指示符变量框架。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="categorical">
<span id="api-categorical"></span><h3><span class="yiyi-st" id="yiyi-1731">分类</span></h3>
<p><span class="yiyi-st" id="yiyi-1732">如果系列属于<code class="docutils literal"><span class="pre">category</span></code>，则<code class="docutils literal"><span class="pre">Series.cat</span></code>可用于更改分类数据。</span><span class="yiyi-st" id="yiyi-1733">此存取器类似于<code class="docutils literal"><span class="pre">Series.dt</span></code>或<code class="docutils literal"><span class="pre">Series.str</span></code>，并具有以下可用的方法和属性：</span></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1734"><a class="reference internal" href="generated/pandas.Series.cat.categories.html#pandas.Series.cat.categories" title="pandas.Series.cat.categories"><code class="xref py py-obj docutils literal"><span class="pre">Series.cat.categories</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1735">这个分类的类别。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1736"><a class="reference internal" href="generated/pandas.Series.cat.ordered.html#pandas.Series.cat.ordered" title="pandas.Series.cat.ordered"><code class="xref py py-obj docutils literal"><span class="pre">Series.cat.ordered</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1737">获取有序属性</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1738"><a class="reference internal" href="generated/pandas.Series.cat.codes.html#pandas.Series.cat.codes" title="pandas.Series.cat.codes"><code class="xref py py-obj docutils literal"><span class="pre">Series.cat.codes</span></code></a></span></td>
<td></td>
</tr>
</tbody>
</table>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1739"><a class="reference internal" href="generated/pandas.Series.cat.rename_categories.html#pandas.Series.cat.rename_categories" title="pandas.Series.cat.rename_categories"><code class="xref py py-obj docutils literal"><span class="pre">Series.cat.rename_categories</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1740">重命名类别。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1741"><a class="reference internal" href="generated/pandas.Series.cat.reorder_categories.html#pandas.Series.cat.reorder_categories" title="pandas.Series.cat.reorder_categories"><code class="xref py py-obj docutils literal"><span class="pre">Series.cat.reorder_categories</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1742">重新排序在new_categories中指定的类别。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1743"><a class="reference internal" href="generated/pandas.Series.cat.add_categories.html#pandas.Series.cat.add_categories" title="pandas.Series.cat.add_categories"><code class="xref py py-obj docutils literal"><span class="pre">Series.cat.add_categories</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1744">添加新类别。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1745"><a class="reference internal" href="generated/pandas.Series.cat.remove_categories.html#pandas.Series.cat.remove_categories" title="pandas.Series.cat.remove_categories"><code class="xref py py-obj docutils literal"><span class="pre">Series.cat.remove_categories</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1746">删除指定的类别。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1747"><a class="reference internal" href="generated/pandas.Series.cat.remove_unused_categories.html#pandas.Series.cat.remove_unused_categories" title="pandas.Series.cat.remove_unused_categories"><code class="xref py py-obj docutils literal"><span class="pre">Series.cat.remove_unused_categories</span></code></a>（\ * args，...）</span></td>
<td><span class="yiyi-st" id="yiyi-1748">删除未使用的类别。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1749"><a class="reference internal" href="generated/pandas.Series.cat.set_categories.html#pandas.Series.cat.set_categories" title="pandas.Series.cat.set_categories"><code class="xref py py-obj docutils literal"><span class="pre">Series.cat.set_categories</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1750">将类别设置为指定的new_categories。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1751"><a class="reference internal" href="generated/pandas.Series.cat.as_ordered.html#pandas.Series.cat.as_ordered" title="pandas.Series.cat.as_ordered"><code class="xref py py-obj docutils literal"><span class="pre">Series.cat.as_ordered</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1752">设置要排序的分类</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1753"><a class="reference internal" href="generated/pandas.Series.cat.as_unordered.html#pandas.Series.cat.as_unordered" title="pandas.Series.cat.as_unordered"><code class="xref py py-obj docutils literal"><span class="pre">Series.cat.as_unordered</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1754">将分类设置为无序</span></td>
</tr>
</tbody>
</table>
<p><span class="yiyi-st" id="yiyi-1755">要创建一系列dtype <code class="docutils literal"><span class="pre">category</span></code>，请使用<code class="docutils literal"><span class="pre">cat</span> <span class="pre">=</span> <span class="pre">s.astype（“category”）</span> </code>。</span></p>
<p><span class="yiyi-st" id="yiyi-1756">以下两个<code class="docutils literal"><span class="pre">Categorical</span></code>构造函数被视为API，但只应在添加排序信息时使用，或在创建分类数据时需要特殊类别：</span></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1757"><a class="reference internal" href="generated/pandas.Categorical.html#pandas.Categorical" title="pandas.Categorical"><code class="xref py py-obj docutils literal"><span class="pre">Categorical</span></code></a>（值[，类别，有序，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1758">表示经典R / S加方式的分类变量</span></td>
</tr>
</tbody>
</table>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1759"><a class="reference internal" href="generated/pandas.Categorical.from_codes.html#pandas.Categorical.from_codes" title="pandas.Categorical.from_codes"><code class="xref py py-obj docutils literal"><span class="pre">Categorical.from_codes</span></code></a>（codes，categories [，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1760">从代码和类别数组创建分类类型。</span></td>
</tr>
</tbody>
</table>
<p><span class="yiyi-st" id="yiyi-1761"><code class="docutils literal"><span class="pre">np.asarray(categorical)</span></code>通过实现数组接口工作。</span><span class="yiyi-st" id="yiyi-1762">请注意，这会将分类转换回numpy数组，因此级别和顺序信息不会保留！</span></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1763"><a class="reference internal" href="generated/pandas.Categorical.__array__.html#pandas.Categorical.__array__" title="pandas.Categorical.__array__"><code class="xref py py-obj docutils literal"><span class="pre">Categorical.__array__</span></code></a>（[dtype]）</span></td>
<td><span class="yiyi-st" id="yiyi-1764">numpy数组接口。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="plotting">
<h3><span class="yiyi-st" id="yiyi-1765">绘制</span></h3>
<p><span class="yiyi-st" id="yiyi-1766"><code class="docutils literal"><span class="pre">Series.plot</span></code>是<code class="docutils literal"><span class="pre">Series.plot.&lt;kind&gt;</span></code>形式的特定绘图方法的可调用方法和命名空间属性。</span></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1767"><a class="reference internal" href="generated/pandas.Series.plot.html#pandas.Series.plot" title="pandas.Series.plot"><code class="xref py py-obj docutils literal"><span class="pre">Series.plot</span></code></a>（[kind，ax，figsize，....]）</span></td>
<td><span class="yiyi-st" id="yiyi-1768">系列绘图存取器和方法</span></td>
</tr>
</tbody>
</table>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1769"><a class="reference internal" href="generated/pandas.Series.plot.area.html#pandas.Series.plot.area" title="pandas.Series.plot.area"><code class="xref py py-obj docutils literal"><span class="pre">Series.plot.area</span></code></a>（\ * \ * kwds）</span></td>
<td><span class="yiyi-st" id="yiyi-1770">面积图</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1771"><a class="reference internal" href="generated/pandas.Series.plot.bar.html#pandas.Series.plot.bar" title="pandas.Series.plot.bar"><code class="xref py py-obj docutils literal"><span class="pre">Series.plot.bar</span></code></a>（\ * \ * kwds）</span></td>
<td><span class="yiyi-st" id="yiyi-1772">垂直条图</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1773"><a class="reference internal" href="generated/pandas.Series.plot.barh.html#pandas.Series.plot.barh" title="pandas.Series.plot.barh"><code class="xref py py-obj docutils literal"><span class="pre">Series.plot.barh</span></code></a>（\ * \ * kwds）</span></td>
<td><span class="yiyi-st" id="yiyi-1774">水平条图</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1775"><a class="reference internal" href="generated/pandas.Series.plot.box.html#pandas.Series.plot.box" title="pandas.Series.plot.box"><code class="xref py py-obj docutils literal"><span class="pre">Series.plot.box</span></code></a>（\ * \ * kwds）</span></td>
<td><span class="yiyi-st" id="yiyi-1776">箱形图</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1777"><a class="reference internal" href="generated/pandas.Series.plot.density.html#pandas.Series.plot.density" title="pandas.Series.plot.density"><code class="xref py py-obj docutils literal"><span class="pre">Series.plot.density</span></code></a>（\ * \ * kwds）</span></td>
<td><span class="yiyi-st" id="yiyi-1778">核密度估计图</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1779"><a class="reference internal" href="generated/pandas.Series.plot.hist.html#pandas.Series.plot.hist" title="pandas.Series.plot.hist"><code class="xref py py-obj docutils literal"><span class="pre">Series.plot.hist</span></code></a>（[bins]）</span></td>
<td><span class="yiyi-st" id="yiyi-1780">直方图</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1781"><a class="reference internal" href="generated/pandas.Series.plot.kde.html#pandas.Series.plot.kde" title="pandas.Series.plot.kde"><code class="xref py py-obj docutils literal"><span class="pre">Series.plot.kde</span></code></a>（\ * \ * kwds）</span></td>
<td><span class="yiyi-st" id="yiyi-1782">核密度估计图</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1783"><a class="reference internal" href="generated/pandas.Series.plot.line.html#pandas.Series.plot.line" title="pandas.Series.plot.line"><code class="xref py py-obj docutils literal"><span class="pre">Series.plot.line</span></code></a>（\ * \ * kwds）</span></td>
<td><span class="yiyi-st" id="yiyi-1784">线图</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1785"><a class="reference internal" href="generated/pandas.Series.plot.pie.html#pandas.Series.plot.pie" title="pandas.Series.plot.pie"><code class="xref py py-obj docutils literal"><span class="pre">Series.plot.pie</span></code></a>（\ * \ * kwds）</span></td>
<td><span class="yiyi-st" id="yiyi-1786">饼形图</span></td>
</tr>
</tbody>
</table>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1787"><a class="reference internal" href="generated/pandas.Series.hist.html#pandas.Series.hist" title="pandas.Series.hist"><code class="xref py py-obj docutils literal"><span class="pre">Series.hist</span></code></a>（[by，ax，grid，xlabelsize，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1788">使用matplotlib绘制输入序列的直方图</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="serialization-io-conversion">
<h3><span class="yiyi-st" id="yiyi-1789">序列化/ IO /转换</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1790"><a class="reference internal" href="generated/pandas.Series.from_csv.html#pandas.Series.from_csv" title="pandas.Series.from_csv"><code class="xref py py-obj docutils literal"><span class="pre">Series.from_csv</span></code></a>（path [，sep，parse_dates，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1791">读取CSV文件（DISCOURAGED，请改用<a class="reference internal" href="generated/pandas.read_csv.html#pandas.read_csv" title="pandas.read_csv"><code class="xref py py-func docutils literal"><span class="pre">pandas.read_csv()</span></code></a>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1792"><a class="reference internal" href="generated/pandas.Series.to_pickle.html#pandas.Series.to_pickle" title="pandas.Series.to_pickle"><code class="xref py py-obj docutils literal"><span class="pre">Series.to_pickle</span></code></a>（path）</span></td>
<td><span class="yiyi-st" id="yiyi-1793">Pickle（序列化）对象到输入文件路径。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1794"><a class="reference internal" href="generated/pandas.Series.to_csv.html#pandas.Series.to_csv" title="pandas.Series.to_csv"><code class="xref py py-obj docutils literal"><span class="pre">Series.to_csv</span></code></a>（[path，index，sep，na_rep，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1795">将系列写入逗号分隔值（csv）文件</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1796"><a class="reference internal" href="generated/pandas.Series.to_dict.html#pandas.Series.to_dict" title="pandas.Series.to_dict"><code class="xref py py-obj docutils literal"><span class="pre">Series.to_dict</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1797">将系列转换为{label  - &gt; value}</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1798"><a class="reference internal" href="generated/pandas.Series.to_frame.html#pandas.Series.to_frame" title="pandas.Series.to_frame"><code class="xref py py-obj docutils literal"><span class="pre">Series.to_frame</span></code></a>（[name]）</span></td>
<td><span class="yiyi-st" id="yiyi-1799">将系列转换为DataFrame</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1800"><a class="reference internal" href="generated/pandas.Series.to_xarray.html#pandas.Series.to_xarray" title="pandas.Series.to_xarray"><code class="xref py py-obj docutils literal"><span class="pre">Series.to_xarray</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1801">从pandas对象返回一个xarray对象。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1802"><a class="reference internal" href="generated/pandas.Series.to_hdf.html#pandas.Series.to_hdf" title="pandas.Series.to_hdf"><code class="xref py py-obj docutils literal"><span class="pre">Series.to_hdf</span></code></a>（path_or_buf，key，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-1803">使用HDFStore将包含的数据写入HDF5文件。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1804"><a class="reference internal" href="generated/pandas.Series.to_sql.html#pandas.Series.to_sql" title="pandas.Series.to_sql"><code class="xref py py-obj docutils literal"><span class="pre">Series.to_sql</span></code></a>（name，con [，flavor，schema，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1805">将存储在DataFrame中的记录写入SQL数据库。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1806"><a class="reference internal" href="generated/pandas.Series.to_msgpack.html#pandas.Series.to_msgpack" title="pandas.Series.to_msgpack"><code class="xref py py-obj docutils literal"><span class="pre">Series.to_msgpack</span></code></a>（[path_or_buf，encoding]）</span></td>
<td><span class="yiyi-st" id="yiyi-1807">msgpack（serialize）对象到输入文件路径</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1808"><a class="reference internal" href="generated/pandas.Series.to_json.html#pandas.Series.to_json" title="pandas.Series.to_json"><code class="xref py py-obj docutils literal"><span class="pre">Series.to_json</span></code></a>（[path_or_buf，orient，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1809">将对象转换为JSON字符串。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1810"><a class="reference internal" href="generated/pandas.Series.to_sparse.html#pandas.Series.to_sparse" title="pandas.Series.to_sparse"><code class="xref py py-obj docutils literal"><span class="pre">Series.to_sparse</span></code></a>（[kind，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-1811">将系列转换为稀疏系列</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1812"><a class="reference internal" href="generated/pandas.Series.to_dense.html#pandas.Series.to_dense" title="pandas.Series.to_dense"><code class="xref py py-obj docutils literal"><span class="pre">Series.to_dense</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1813">返回NDFrame的密集表示（而不是稀疏）</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1814"><a class="reference internal" href="generated/pandas.Series.to_string.html#pandas.Series.to_string" title="pandas.Series.to_string"><code class="xref py py-obj docutils literal"><span class="pre">Series.to_string</span></code></a>（[buf，na_rep，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1815">呈现系列的字符串表示形式</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1816"><a class="reference internal" href="generated/pandas.Series.to_clipboard.html#pandas.Series.to_clipboard" title="pandas.Series.to_clipboard"><code class="xref py py-obj docutils literal"><span class="pre">Series.to_clipboard</span></code></a>（[excel，sep]）</span></td>
<td><span class="yiyi-st" id="yiyi-1817">尝试将对象的文本表示写入系统剪贴板例如，可以将其粘贴到Excel中。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="sparse-methods">
<h3><span class="yiyi-st" id="yiyi-1818">稀疏方法</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1819"><a class="reference internal" href="generated/pandas.SparseSeries.to_coo.html#pandas.SparseSeries.to_coo" title="pandas.SparseSeries.to_coo"><code class="xref py py-obj docutils literal"><span class="pre">SparseSeries.to_coo</span></code></a>（[row_levels，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1820">从带有MultiIndex的SparseSeries创建scipy.sparse.coo_matrix。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1821"><a class="reference internal" href="generated/pandas.SparseSeries.from_coo.html#pandas.SparseSeries.from_coo" title="pandas.SparseSeries.from_coo"><code class="xref py py-obj docutils literal"><span class="pre">SparseSeries.from_coo</span></code></a>（A [，dense_index]）</span></td>
<td><span class="yiyi-st" id="yiyi-1822">从scipy.sparse.coo_matrix创建SparseSeries。</span></td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section" id="dataframe">
<span id="api-dataframe"></span><h2><span class="yiyi-st" id="yiyi-1823">数据帧</span></h2>
<div class="section" id="id1">
<h3><span class="yiyi-st" id="yiyi-1824">构造</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1825"><a class="reference internal" href="generated/pandas.DataFrame.html#pandas.DataFrame" title="pandas.DataFrame"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame</span></code></a>（[data，index，columns，dtype，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-1826">二维大小可变的，潜在异质的表格数据结构，带有标记的轴（行和列）。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="attributes-and-underlying-data">
<h3><span class="yiyi-st" id="yiyi-1827">属性和底层数据</span></h3>
<p><span class="yiyi-st" id="yiyi-1828"><strong>轴</strong></span></p>
<blockquote>
<div><ul class="simple">
<li><span class="yiyi-st" id="yiyi-1829"><strong>index</strong>：行标签</span></li>
<li><span class="yiyi-st" id="yiyi-1830"><strong>列</strong>：列标签</span></li>
</ul>
</div></blockquote>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1831"><a class="reference internal" href="generated/pandas.DataFrame.as_matrix.html#pandas.DataFrame.as_matrix" title="pandas.DataFrame.as_matrix"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.as_matrix</span></code></a>（[columns]）</span></td>
<td><span class="yiyi-st" id="yiyi-1832">将帧转换为其Numpy数组表示。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1833"><a class="reference internal" href="generated/pandas.DataFrame.dtypes.html#pandas.DataFrame.dtypes" title="pandas.DataFrame.dtypes"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.dtypes</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1834">返回此对象中的dtype。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1835"><a class="reference internal" href="generated/pandas.DataFrame.ftypes.html#pandas.DataFrame.ftypes" title="pandas.DataFrame.ftypes"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.ftypes</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1836">返回此对象中的ftypes（稀疏/密集和dtype的指示）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1837"><a class="reference internal" href="generated/pandas.DataFrame.get_dtype_counts.html#pandas.DataFrame.get_dtype_counts" title="pandas.DataFrame.get_dtype_counts"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.get_dtype_counts</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1838">返回此对象中的dtypes的计数。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1839"><a class="reference internal" href="generated/pandas.DataFrame.get_ftype_counts.html#pandas.DataFrame.get_ftype_counts" title="pandas.DataFrame.get_ftype_counts"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.get_ftype_counts</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1840">返回此对象中的ftypes的计数。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1841"><a class="reference internal" href="generated/pandas.DataFrame.select_dtypes.html#pandas.DataFrame.select_dtypes" title="pandas.DataFrame.select_dtypes"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.select_dtypes</span></code></a>（[include，exclude]）</span></td>
<td><span class="yiyi-st" id="yiyi-1842">返回基于其<code class="docutils literal"><span class="pre">dtype</span></code>包含/排除列的DataFrame子集。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1843"><a class="reference internal" href="generated/pandas.DataFrame.values.html#pandas.DataFrame.values" title="pandas.DataFrame.values"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.values</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1844">NDFrame的块状表示</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1845"><a class="reference internal" href="generated/pandas.DataFrame.axes.html#pandas.DataFrame.axes" title="pandas.DataFrame.axes"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.axes</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1846">返回具有行轴标签和列轴标签作为唯一成员的列表。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1847"><a class="reference internal" href="generated/pandas.DataFrame.ndim.html#pandas.DataFrame.ndim" title="pandas.DataFrame.ndim"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.ndim</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1848">轴数/阵列尺寸</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1849"><a class="reference internal" href="generated/pandas.DataFrame.size.html#pandas.DataFrame.size" title="pandas.DataFrame.size"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.size</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1850">NDFrame中的元素数</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1851"><a class="reference internal" href="generated/pandas.DataFrame.shape.html#pandas.DataFrame.shape" title="pandas.DataFrame.shape"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.shape</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1852">返回一个表示DataFrame的维度的元组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1853"><a class="reference internal" href="generated/pandas.DataFrame.memory_usage.html#pandas.DataFrame.memory_usage" title="pandas.DataFrame.memory_usage"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.memory_usage</span></code></a>（[index，deep]）</span></td>
<td><span class="yiyi-st" id="yiyi-1854">DataFrame列的内存使用情况。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id2">
<h3><span class="yiyi-st" id="yiyi-1855">转换</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1856"><a class="reference internal" href="generated/pandas.DataFrame.astype.html#pandas.DataFrame.astype" title="pandas.DataFrame.astype"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.astype</span></code></a>（dtype [，copy，raise_on_error]）</span></td>
<td><span class="yiyi-st" id="yiyi-1857">投射对象以输入numpy.dtype</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1858"><a class="reference internal" href="generated/pandas.DataFrame.convert_objects.html#pandas.DataFrame.convert_objects" title="pandas.DataFrame.convert_objects"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.convert_objects</span></code></a>（[convert_dates，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1859">已弃用。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1860"><a class="reference internal" href="generated/pandas.DataFrame.copy.html#pandas.DataFrame.copy" title="pandas.DataFrame.copy"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.copy</span></code></a>（[deep]）</span></td>
<td><span class="yiyi-st" id="yiyi-1861">复制此对象数据。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1862"><a class="reference internal" href="generated/pandas.DataFrame.isnull.html#pandas.DataFrame.isnull" title="pandas.DataFrame.isnull"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.isnull</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1863">返回一个布尔大小相同的对象，指示值是否为null。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1864"><a class="reference internal" href="generated/pandas.DataFrame.notnull.html#pandas.DataFrame.notnull" title="pandas.DataFrame.notnull"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.notnull</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1865">返回一个布尔大小相同的对象，指示这些值是否为空。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id3">
<h3><span class="yiyi-st" id="yiyi-1866">索引，迭代</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1867"><a class="reference internal" href="generated/pandas.DataFrame.head.html#pandas.DataFrame.head" title="pandas.DataFrame.head"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.head</span></code></a>（[n]）</span></td>
<td><span class="yiyi-st" id="yiyi-1868">返回前n行</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1869"><a class="reference internal" href="generated/pandas.DataFrame.at.html#pandas.DataFrame.at" title="pandas.DataFrame.at"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.at</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1870">基于快速标签的标量访问器</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1871"><a class="reference internal" href="generated/pandas.DataFrame.iat.html#pandas.DataFrame.iat" title="pandas.DataFrame.iat"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.iat</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1872">快速整数位置标量存取器。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1873"><a class="reference internal" href="generated/pandas.DataFrame.ix.html#pandas.DataFrame.ix" title="pandas.DataFrame.ix"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.ix</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1874">主要是基于标签位置的索引器，具有整数位置后备。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1875"><a class="reference internal" href="generated/pandas.DataFrame.loc.html#pandas.DataFrame.loc" title="pandas.DataFrame.loc"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.loc</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1876">纯标签位置索引器，用于按标签选择。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1877"><a class="reference internal" href="generated/pandas.DataFrame.iloc.html#pandas.DataFrame.iloc" title="pandas.DataFrame.iloc"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.iloc</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-1878">纯粹基于整数位置的索引，用于按位置选择。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1879"><a class="reference internal" href="generated/pandas.DataFrame.insert.html#pandas.DataFrame.insert" title="pandas.DataFrame.insert"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.insert</span></code></a>（loc，column，value [，...]</span></td>
<td><span class="yiyi-st" id="yiyi-1880">在指定位置将列插入DataFrame。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1881"><a class="reference internal" href="generated/pandas.DataFrame.__iter__.html#pandas.DataFrame.__iter__" title="pandas.DataFrame.__iter__"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.__iter__</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1882">在信息轴上迭代</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1883"><a class="reference internal" href="generated/pandas.DataFrame.iteritems.html#pandas.DataFrame.iteritems" title="pandas.DataFrame.iteritems"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.iteritems</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1884">迭代器结束（列名，系列）对。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1885"><a class="reference internal" href="generated/pandas.DataFrame.iterrows.html#pandas.DataFrame.iterrows" title="pandas.DataFrame.iterrows"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.iterrows</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1886">将DataFrame行重复为（索引，系列）对。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1887"><a class="reference internal" href="generated/pandas.DataFrame.itertuples.html#pandas.DataFrame.itertuples" title="pandas.DataFrame.itertuples"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.itertuples</span></code></a>（[index，name]）</span></td>
<td><span class="yiyi-st" id="yiyi-1888">将DataFrame行迭代为namedtuples，索引值作为元组的第一个元素。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1889"><a class="reference internal" href="generated/pandas.DataFrame.lookup.html#pandas.DataFrame.lookup" title="pandas.DataFrame.lookup"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.lookup</span></code></a>（row_labels，col_labels）</span></td>
<td><span class="yiyi-st" id="yiyi-1890">DataFrame基于标签的“花式索引”功能。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1891"><a class="reference internal" href="generated/pandas.DataFrame.pop.html#pandas.DataFrame.pop" title="pandas.DataFrame.pop"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.pop</span></code></a>（item）</span></td>
<td><span class="yiyi-st" id="yiyi-1892">返回项目并从框架中删除。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1893"><a class="reference internal" href="generated/pandas.DataFrame.tail.html#pandas.DataFrame.tail" title="pandas.DataFrame.tail"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.tail</span></code></a>（[n]）</span></td>
<td><span class="yiyi-st" id="yiyi-1894">返回最后n行</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1895"><a class="reference internal" href="generated/pandas.DataFrame.xs.html#pandas.DataFrame.xs" title="pandas.DataFrame.xs"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.xs</span></code></a>（键[，axis，level，drop_level]）</span></td>
<td><span class="yiyi-st" id="yiyi-1896">从Series / DataFrame返回横截面（行或列）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1897"><a class="reference internal" href="generated/pandas.DataFrame.isin.html#pandas.DataFrame.isin" title="pandas.DataFrame.isin"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.isin</span></code></a>（values）</span></td>
<td><span class="yiyi-st" id="yiyi-1898">返回布尔值DataFrame，显示DataFrame中的每个元素是否包含在值中。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1899"><a class="reference internal" href="generated/pandas.DataFrame.where.html#pandas.DataFrame.where" title="pandas.DataFrame.where"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.where</span></code></a>（cond [，other，inplace，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1900">返回一个与self相同形状的对象，其对应的条目来自self，其中cond为True，否则为其他对象。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1901"><a class="reference internal" href="generated/pandas.DataFrame.mask.html#pandas.DataFrame.mask" title="pandas.DataFrame.mask"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.mask</span></code></a>（cond [，other，inplace，axis，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1902">返回一个与self相同形状的对象，并且其对应的条目来自self，其中cond是False，否则是来自其他。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1903"><a class="reference internal" href="generated/pandas.DataFrame.query.html#pandas.DataFrame.query" title="pandas.DataFrame.query"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.query</span></code></a>（expr [，inplace]）</span></td>
<td><span class="yiyi-st" id="yiyi-1904">使用布尔表达式查询框架的列。</span></td>
</tr>
</tbody>
</table>
<p><span class="yiyi-st" id="yiyi-1905">有关<code class="docutils literal"><span class="pre">.at</span></code>，<code class="docutils literal"><span class="pre">.iat</span></code>，<code class="docutils literal"><span class="pre">.ix</span></code>，<code class="docutils literal"><span class="pre">.loc</span></code>和<code class="docutils literal"><span class="pre">.iloc</span></code>，请参阅<a class="reference internal" href="indexing.html#indexing"><span class="std std-ref">indexing documentation</span></a>。</span></p>
</div>
<div class="section" id="id4">
<h3><span class="yiyi-st" id="yiyi-1906">二进制运算符函数</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1907"><a class="reference internal" href="generated/pandas.DataFrame.add.html#pandas.DataFrame.add" title="pandas.DataFrame.add"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.add</span></code></a>（其他[，axis，level，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-1908">添加数据帧和其他，元素方式（二进制运算符<cite>add</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1909"><a class="reference internal" href="generated/pandas.DataFrame.sub.html#pandas.DataFrame.sub" title="pandas.DataFrame.sub"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.sub</span></code></a>（其他[，axis，level，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-1910">减数据帧和其他，元素方式（二元运算符<cite>子</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1911"><a class="reference internal" href="generated/pandas.DataFrame.mul.html#pandas.DataFrame.mul" title="pandas.DataFrame.mul"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.mul</span></code></a>（其他[，axis，level，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-1912">数据帧和其他元素乘法（二元运算符<cite>mul</cite>）的乘法。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1913"><a class="reference internal" href="generated/pandas.DataFrame.div.html#pandas.DataFrame.div" title="pandas.DataFrame.div"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.div</span></code></a>（其他[，axis，level，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-1914">数据帧和其他元素浮点划分（二元运算符<cite>truediv</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1915"><a class="reference internal" href="generated/pandas.DataFrame.truediv.html#pandas.DataFrame.truediv" title="pandas.DataFrame.truediv"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.truediv</span></code></a>（其他[，axis，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1916">数据帧和其他元素浮点划分（二元运算符<cite>truediv</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1917"><a class="reference internal" href="generated/pandas.DataFrame.floordiv.html#pandas.DataFrame.floordiv" title="pandas.DataFrame.floordiv"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.floordiv</span></code></a>（其他[，axis，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1918">数据帧和其他元素整数（二进制运算符<cite>floordiv</cite>）的整数除法。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1919"><a class="reference internal" href="generated/pandas.DataFrame.mod.html#pandas.DataFrame.mod" title="pandas.DataFrame.mod"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.mod</span></code></a>（其他[，axis，level，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-1920">数据帧和其他元素模式（二元运算符<cite>mod</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1921"><a class="reference internal" href="generated/pandas.DataFrame.pow.html#pandas.DataFrame.pow" title="pandas.DataFrame.pow"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.pow</span></code></a>（其他[，axis，level，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-1922">数据帧和其他元指数的幂指数（二元运算符<cite>pow</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1923"><a class="reference internal" href="generated/pandas.DataFrame.radd.html#pandas.DataFrame.radd" title="pandas.DataFrame.radd"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.radd</span></code></a>（其他[，axis，level，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-1924">添加数据帧和其他，元素方式（二元运算符<cite>radd</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1925"><a class="reference internal" href="generated/pandas.DataFrame.rsub.html#pandas.DataFrame.rsub" title="pandas.DataFrame.rsub"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.rsub</span></code></a>（其他[，axis，level，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-1926">减数据帧和其他，元素方式（二元运算符<cite>rsub</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1927"><a class="reference internal" href="generated/pandas.DataFrame.rmul.html#pandas.DataFrame.rmul" title="pandas.DataFrame.rmul"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.rmul</span></code></a>（其他[，axis，level，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-1928">数据帧和其他元素乘法（二元运算符<cite>rmul</cite>）的乘法。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1929"><a class="reference internal" href="generated/pandas.DataFrame.rdiv.html#pandas.DataFrame.rdiv" title="pandas.DataFrame.rdiv"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.rdiv</span></code></a>（其他[，axis，level，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-1930">数据帧的浮动划分和其他，元素方式（二元运算符<cite>rtruediv</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1931"><a class="reference internal" href="generated/pandas.DataFrame.rtruediv.html#pandas.DataFrame.rtruediv" title="pandas.DataFrame.rtruediv"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.rtruediv</span></code></a>（其他[，axis，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1932">数据帧的浮动划分和其他，元素方式（二元运算符<cite>rtruediv</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1933"><a class="reference internal" href="generated/pandas.DataFrame.rfloordiv.html#pandas.DataFrame.rfloordiv" title="pandas.DataFrame.rfloordiv"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.rfloordiv</span></code></a>（其他[，axis，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1934">数据帧和其他元素整数（二进制运算符<cite>rfloordiv</cite>）的整数除法。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1935"><a class="reference internal" href="generated/pandas.DataFrame.rmod.html#pandas.DataFrame.rmod" title="pandas.DataFrame.rmod"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.rmod</span></code></a>（其他[，axis，level，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-1936">数据帧模式和其他，元素方式（二元算符<cite>rmod</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1937"><a class="reference internal" href="generated/pandas.DataFrame.rpow.html#pandas.DataFrame.rpow" title="pandas.DataFrame.rpow"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.rpow</span></code></a>（其他[，axis，level，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-1938">数据帧和其他元指数的幂指数（二元运算符<cite>rpow</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1939"><a class="reference internal" href="generated/pandas.DataFrame.lt.html#pandas.DataFrame.lt" title="pandas.DataFrame.lt"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.lt</span></code></a>（其他[，axis，level]）</span></td>
<td><span class="yiyi-st" id="yiyi-1940">用于灵活比较方法的包装器</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1941"><a class="reference internal" href="generated/pandas.DataFrame.gt.html#pandas.DataFrame.gt" title="pandas.DataFrame.gt"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.gt</span></code></a>（其他[，axis，level]）</span></td>
<td><span class="yiyi-st" id="yiyi-1942">用于灵活比较方法的包装器gt</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1943"><a class="reference internal" href="generated/pandas.DataFrame.le.html#pandas.DataFrame.le" title="pandas.DataFrame.le"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.le</span></code></a>（其他[，轴，级别]）</span></td>
<td><span class="yiyi-st" id="yiyi-1944">用于灵活比较方法的包装器</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1945"><a class="reference internal" href="generated/pandas.DataFrame.ge.html#pandas.DataFrame.ge" title="pandas.DataFrame.ge"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.ge</span></code></a>（其他[，axis，level]）</span></td>
<td><span class="yiyi-st" id="yiyi-1946">用于灵活比较方法的包装器</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1947"><a class="reference internal" href="generated/pandas.DataFrame.ne.html#pandas.DataFrame.ne" title="pandas.DataFrame.ne"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.ne</span></code></a>（其他[，axis，level]）</span></td>
<td><span class="yiyi-st" id="yiyi-1948">用于灵活比较方法的包装器</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1949"><a class="reference internal" href="generated/pandas.DataFrame.eq.html#pandas.DataFrame.eq" title="pandas.DataFrame.eq"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.eq</span></code></a>（其他[，axis，level]）</span></td>
<td><span class="yiyi-st" id="yiyi-1950">用于灵活比较方法的包装器</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1951"><a class="reference internal" href="generated/pandas.DataFrame.combine.html#pandas.DataFrame.combine" title="pandas.DataFrame.combine"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.combine</span></code></a>（other，func [，fill_value，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1952">添加两个DataFrame对象，不传播NaN值，因此如果为a</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1953"><a class="reference internal" href="generated/pandas.DataFrame.combine_first.html#pandas.DataFrame.combine_first" title="pandas.DataFrame.combine_first"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.combine_first</span></code></a>（other）</span></td>
<td><span class="yiyi-st" id="yiyi-1954">在调用方法的帧中组合两个DataFrame对象和默认非空值。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id5">
<h3><span class="yiyi-st" id="yiyi-1955">功能应用，Group By&amp; Window</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1956"><a class="reference internal" href="generated/pandas.DataFrame.apply.html#pandas.DataFrame.apply" title="pandas.DataFrame.apply"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.apply</span></code></a>（func [，axis，broadcast，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1957">沿DataFrame的输入轴应用函数。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1958"><a class="reference internal" href="generated/pandas.DataFrame.applymap.html#pandas.DataFrame.applymap" title="pandas.DataFrame.applymap"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.applymap</span></code></a>（func）</span></td>
<td><span class="yiyi-st" id="yiyi-1959">将一个函数应用到要单元操作的DataFrame，即</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1960"><a class="reference internal" href="generated/pandas.DataFrame.groupby.html#pandas.DataFrame.groupby" title="pandas.DataFrame.groupby"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.groupby</span></code></a>（[by，axis，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1961">使用mapper的组系列（dict或key函数，将给定函数应用于组，将结果返回为系列）或通过一系列列。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1962"><a class="reference internal" href="generated/pandas.DataFrame.rolling.html#pandas.DataFrame.rolling" title="pandas.DataFrame.rolling"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.rolling</span></code></a>（window [，min_periods，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1963">提供滚动窗口计算。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1964"><a class="reference internal" href="generated/pandas.DataFrame.expanding.html#pandas.DataFrame.expanding" title="pandas.DataFrame.expanding"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.expanding</span></code></a>（[min_periods，freq，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1965">提供扩展转换。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1966"><a class="reference internal" href="generated/pandas.DataFrame.ewm.html#pandas.DataFrame.ewm" title="pandas.DataFrame.ewm"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.ewm</span></code></a>（[com，span，halflife，alpha，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1967">提供指数加权函数</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="api-dataframe-stats">
<span id="id6"></span><h3><span class="yiyi-st" id="yiyi-1968">计算/描述性统计</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1969"><a class="reference internal" href="generated/pandas.DataFrame.abs.html#pandas.DataFrame.abs" title="pandas.DataFrame.abs"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.abs</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-1970">返回具有绝对值的对象，仅适用于全部为数字的对象。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1971"><a class="reference internal" href="generated/pandas.DataFrame.all.html#pandas.DataFrame.all" title="pandas.DataFrame.all"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.all</span></code></a>（[axis，bool_only，skipna，level]）</span></td>
<td><span class="yiyi-st" id="yiyi-1972">返回所有元素是否超过请求的轴的True</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1973"><a class="reference internal" href="generated/pandas.DataFrame.any.html#pandas.DataFrame.any" title="pandas.DataFrame.any"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.any</span></code></a>（[axis，bool_only，skipna，level]）</span></td>
<td><span class="yiyi-st" id="yiyi-1974">返回任何元素是否超过请求的轴为True</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1975"><a class="reference internal" href="generated/pandas.DataFrame.clip.html#pandas.DataFrame.clip" title="pandas.DataFrame.clip"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.clip</span></code></a>（[lower，upper，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1976">修整输入阈值处的值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1977"><a class="reference internal" href="generated/pandas.DataFrame.clip_lower.html#pandas.DataFrame.clip_lower" title="pandas.DataFrame.clip_lower"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.clip_lower</span></code></a>（threshold [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1978">返回具有低于给定值的值的输入的副本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1979"><a class="reference internal" href="generated/pandas.DataFrame.clip_upper.html#pandas.DataFrame.clip_upper" title="pandas.DataFrame.clip_upper"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.clip_upper</span></code></a>（threshold [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-1980">返回具有高于给定值的值的输入的副本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1981"><a class="reference internal" href="generated/pandas.DataFrame.corr.html#pandas.DataFrame.corr" title="pandas.DataFrame.corr"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.corr</span></code></a>（[method，min_periods]）</span></td>
<td><span class="yiyi-st" id="yiyi-1982">计算列的成对相关性，不包括NA /空值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1983"><a class="reference internal" href="generated/pandas.DataFrame.corrwith.html#pandas.DataFrame.corrwith" title="pandas.DataFrame.corrwith"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.corrwith</span></code></a>（other [，axis，drop]）</span></td>
<td><span class="yiyi-st" id="yiyi-1984">计算两个DataFrame对象的行或列之间的成对相关性。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1985"><a class="reference internal" href="generated/pandas.DataFrame.count.html#pandas.DataFrame.count" title="pandas.DataFrame.count"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.count</span></code></a>（[axis，level，numeric_only]）</span></td>
<td><span class="yiyi-st" id="yiyi-1986">返回具有在所请求轴上的非NA /零值观测数的返回系列。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1987"><a class="reference internal" href="generated/pandas.DataFrame.cov.html#pandas.DataFrame.cov" title="pandas.DataFrame.cov"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.cov</span></code></a>（[min_periods]）</span></td>
<td><span class="yiyi-st" id="yiyi-1988">计算列的成对协方差，不包括NA /空值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1989"><a class="reference internal" href="generated/pandas.DataFrame.cummax.html#pandas.DataFrame.cummax" title="pandas.DataFrame.cummax"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.cummax</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-1990">返回请求轴上的累积最大值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1991"><a class="reference internal" href="generated/pandas.DataFrame.cummin.html#pandas.DataFrame.cummin" title="pandas.DataFrame.cummin"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.cummin</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-1992">返回所请求轴上的累积最小值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1993"><a class="reference internal" href="generated/pandas.DataFrame.cumprod.html#pandas.DataFrame.cumprod" title="pandas.DataFrame.cumprod"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.cumprod</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-1994">通过请求轴返回累积乘积。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1995"><a class="reference internal" href="generated/pandas.DataFrame.cumsum.html#pandas.DataFrame.cumsum" title="pandas.DataFrame.cumsum"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.cumsum</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-1996">通过请求轴返回累积和。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-1997"><a class="reference internal" href="generated/pandas.DataFrame.describe.html#pandas.DataFrame.describe" title="pandas.DataFrame.describe"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.describe</span></code></a>（[percentiles，include，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-1998">生成各种汇总统计，不包括NaN值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-1999"><a class="reference internal" href="generated/pandas.DataFrame.diff.html#pandas.DataFrame.diff" title="pandas.DataFrame.diff"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.diff</span></code></a>（[periods，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2000">对象的第一离散差异</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2001"><a class="reference internal" href="generated/pandas.DataFrame.eval.html#pandas.DataFrame.eval" title="pandas.DataFrame.eval"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.eval</span></code></a>（expr [，inplace]）</span></td>
<td><span class="yiyi-st" id="yiyi-2002">在调用DataFrame实例的上下文中评估表达式。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2003"><a class="reference internal" href="generated/pandas.DataFrame.kurt.html#pandas.DataFrame.kurt" title="pandas.DataFrame.kurt"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.kurt</span></code></a>（[axis，skipna，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2004">使用Fisher的峰度定义（kurtosis of normal == 0.0）返回无偏的峰度超过请求的轴。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2005"><a class="reference internal" href="generated/pandas.DataFrame.mad.html#pandas.DataFrame.mad" title="pandas.DataFrame.mad"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.mad</span></code></a>（[axis，skipna，level]）</span></td>
<td><span class="yiyi-st" id="yiyi-2006">返回请求轴的值的平均绝对偏差</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2007"><a class="reference internal" href="generated/pandas.DataFrame.max.html#pandas.DataFrame.max" title="pandas.DataFrame.max"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.max</span></code></a>（[axis，skipna，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2008">此方法返回对象中值的最大值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2009"><a class="reference internal" href="generated/pandas.DataFrame.mean.html#pandas.DataFrame.mean" title="pandas.DataFrame.mean"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.mean</span></code></a>（[axis，skipna，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2010">返回请求轴的值的平均值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2011"><a class="reference internal" href="generated/pandas.DataFrame.median.html#pandas.DataFrame.median" title="pandas.DataFrame.median"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.median</span></code></a>（[axis，skipna，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2012">返回请求轴的值的中值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2013"><a class="reference internal" href="generated/pandas.DataFrame.min.html#pandas.DataFrame.min" title="pandas.DataFrame.min"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.min</span></code></a>（[axis，skipna，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2014">此方法返回对象中值的最小值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2015"><a class="reference internal" href="generated/pandas.DataFrame.mode.html#pandas.DataFrame.mode" title="pandas.DataFrame.mode"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.mode</span></code></a>（[axis，numeric_only]）</span></td>
<td><span class="yiyi-st" id="yiyi-2016">获取所选轴上每个元素的模式。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2017"><a class="reference internal" href="generated/pandas.DataFrame.pct_change.html#pandas.DataFrame.pct_change" title="pandas.DataFrame.pct_change"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.pct_change</span></code></a>（[periods，fill_method，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2018">给定周期数的百分比变化。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2019"><a class="reference internal" href="generated/pandas.DataFrame.prod.html#pandas.DataFrame.prod" title="pandas.DataFrame.prod"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.prod</span></code></a>（[axis，skipna，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2020">返回请求轴的值的乘积</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2021"><a class="reference internal" href="generated/pandas.DataFrame.quantile.html#pandas.DataFrame.quantile" title="pandas.DataFrame.quantile"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.quantile</span></code></a>（[q，axis，numeric_only，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2022">在给定分位数的返回值超过请求的轴，一个数字。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2023"><a class="reference internal" href="generated/pandas.DataFrame.rank.html#pandas.DataFrame.rank" title="pandas.DataFrame.rank"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.rank</span></code></a>（[axis，method，numeric_only，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2024">沿轴计算数值数据（1到n）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2025"><a class="reference internal" href="generated/pandas.DataFrame.round.html#pandas.DataFrame.round" title="pandas.DataFrame.round"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.round</span></code></a>（[小数]）</span></td>
<td><span class="yiyi-st" id="yiyi-2026">将DataFrame舍入到可变小数位数。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2027"><a class="reference internal" href="generated/pandas.DataFrame.sem.html#pandas.DataFrame.sem" title="pandas.DataFrame.sem"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.sem</span></code></a>（[axis，skipna，level，ddof，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2028">返回所要求轴的平均值的无偏差标准误差。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2029"><a class="reference internal" href="generated/pandas.DataFrame.skew.html#pandas.DataFrame.skew" title="pandas.DataFrame.skew"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.skew</span></code></a>（[axis，skipna，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2030">返回所请求轴的无偏斜</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2031"><a class="reference internal" href="generated/pandas.DataFrame.sum.html#pandas.DataFrame.sum" title="pandas.DataFrame.sum"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.sum</span></code></a>（[axis，skipna，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2032">返回请求轴的值的总和</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2033"><a class="reference internal" href="generated/pandas.DataFrame.std.html#pandas.DataFrame.std" title="pandas.DataFrame.std"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.std</span></code></a>（[axis，skipna，level，ddof，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2034">返回样品标准偏差超过请求的轴。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2035"><a class="reference internal" href="generated/pandas.DataFrame.var.html#pandas.DataFrame.var" title="pandas.DataFrame.var"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.var</span></code></a>（[axis，skipna，level，ddof，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2036">返回与请求轴无关的方差。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id7">
<h3><span class="yiyi-st" id="yiyi-2037">重新索引/选择/标签操作</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2038"><a class="reference internal" href="generated/pandas.DataFrame.add_prefix.html#pandas.DataFrame.add_prefix" title="pandas.DataFrame.add_prefix"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.add_prefix</span></code></a>（prefix）</span></td>
<td><span class="yiyi-st" id="yiyi-2039">将前缀字符串与面板项名称连接。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2040"><a class="reference internal" href="generated/pandas.DataFrame.add_suffix.html#pandas.DataFrame.add_suffix" title="pandas.DataFrame.add_suffix"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.add_suffix</span></code></a>（suffix）</span></td>
<td><span class="yiyi-st" id="yiyi-2041">将后缀字符串与面板项名称连接。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2042"><a class="reference internal" href="generated/pandas.DataFrame.align.html#pandas.DataFrame.align" title="pandas.DataFrame.align"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.align</span></code></a>（其他[，join，axis，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2043">将它们的轴上的两个对象与</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2044"><a class="reference internal" href="generated/pandas.DataFrame.drop.html#pandas.DataFrame.drop" title="pandas.DataFrame.drop"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.drop</span></code></a>（标签[，axis，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2045">返回请求轴中标签已删除的新对象。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2046"><a class="reference internal" href="generated/pandas.DataFrame.drop_duplicates.html#pandas.DataFrame.drop_duplicates" title="pandas.DataFrame.drop_duplicates"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.drop_duplicates</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2047">返回已删除重复行的DataFrame（仅可选）</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2048"><a class="reference internal" href="generated/pandas.DataFrame.duplicated.html#pandas.DataFrame.duplicated" title="pandas.DataFrame.duplicated"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.duplicated</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2049">返回boolean表示重复行的系列，仅可选</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2050"><a class="reference internal" href="generated/pandas.DataFrame.equals.html#pandas.DataFrame.equals" title="pandas.DataFrame.equals"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.equals</span></code></a>（other）</span></td>
<td><span class="yiyi-st" id="yiyi-2051">确定两个NDFrame对象是否包含相同的元素。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2052"><a class="reference internal" href="generated/pandas.DataFrame.filter.html#pandas.DataFrame.filter" title="pandas.DataFrame.filter"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.filter</span></code></a>（[items，like，regex，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2053">子集根据指定索引中的标签的数据帧的行或列。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2054"><a class="reference internal" href="generated/pandas.DataFrame.first.html#pandas.DataFrame.first" title="pandas.DataFrame.first"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.first</span></code></a>（offset）</span></td>
<td><span class="yiyi-st" id="yiyi-2055">用于基于日期偏移对时间序列数据的初始时间进行子集化的便利方法。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2056"><a class="reference internal" href="generated/pandas.DataFrame.head.html#pandas.DataFrame.head" title="pandas.DataFrame.head"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.head</span></code></a>（[n]）</span></td>
<td><span class="yiyi-st" id="yiyi-2057">返回前n行</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2058"><a class="reference internal" href="generated/pandas.DataFrame.idxmax.html#pandas.DataFrame.idxmax" title="pandas.DataFrame.idxmax"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.idxmax</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-2059">在请求的轴上的第一次出现的最大值的返回索引。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2060"><a class="reference internal" href="generated/pandas.DataFrame.idxmin.html#pandas.DataFrame.idxmin" title="pandas.DataFrame.idxmin"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.idxmin</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-2061">请求轴上的第一次出现的最小值的返回索引。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2062"><a class="reference internal" href="generated/pandas.DataFrame.last.html#pandas.DataFrame.last" title="pandas.DataFrame.last"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.last</span></code></a>（offset）</span></td>
<td><span class="yiyi-st" id="yiyi-2063">基于日期偏移对时间序列数据的最终周期子集化的便利方法。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2064"><a class="reference internal" href="generated/pandas.DataFrame.reindex.html#pandas.DataFrame.reindex" title="pandas.DataFrame.reindex"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.reindex</span></code></a>（[index，columns]）</span></td>
<td><span class="yiyi-st" id="yiyi-2065">使用可选填充逻辑将DataFrame与新索引一致，将NA / NaN放在前一个索引中没有值的位置。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2066"><a class="reference internal" href="generated/pandas.DataFrame.reindex_axis.html#pandas.DataFrame.reindex_axis" title="pandas.DataFrame.reindex_axis"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.reindex_axis</span></code></a>（标签[，axis，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2067">使用可选填充逻辑将输入对象与新索引一致，将NA / NaN放在前一个索引中没有值的位置。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2068"><a class="reference internal" href="generated/pandas.DataFrame.reindex_like.html#pandas.DataFrame.reindex_like" title="pandas.DataFrame.reindex_like"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.reindex_like</span></code></a>（other [，method，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2069">将具有匹配索引的对象返回给我自己。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2070"><a class="reference internal" href="generated/pandas.DataFrame.rename.html#pandas.DataFrame.rename" title="pandas.DataFrame.rename"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.rename</span></code></a>（[index，columns]）</span></td>
<td><span class="yiyi-st" id="yiyi-2071">改变轴输入功能。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2072"><a class="reference internal" href="generated/pandas.DataFrame.rename_axis.html#pandas.DataFrame.rename_axis" title="pandas.DataFrame.rename_axis"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.rename_axis</span></code></a>（mapper [，axis，copy，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2073">使用输入函数或函数修改索引和/或列。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2074"><a class="reference internal" href="generated/pandas.DataFrame.reset_index.html#pandas.DataFrame.reset_index" title="pandas.DataFrame.reset_index"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.reset_index</span></code></a>（[level，drop，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2075">对于具有多级索引的DataFrame，在索引名称下的列中返回带有标签信息的新DataFrame，默认为“level_0”，“level_1”等。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2076"><a class="reference internal" href="generated/pandas.DataFrame.sample.html#pandas.DataFrame.sample" title="pandas.DataFrame.sample"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.sample</span></code></a>（[n，frac，replace，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2077">从对象的轴返回项目的随机样本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2078"><a class="reference internal" href="generated/pandas.DataFrame.select.html#pandas.DataFrame.select" title="pandas.DataFrame.select"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.select</span></code></a>（crit [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2079">返回与轴标签匹配条件相对应的数据</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2080"><a class="reference internal" href="generated/pandas.DataFrame.set_index.html#pandas.DataFrame.set_index" title="pandas.DataFrame.set_index"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.set_index</span></code></a>（keys [，drop，append，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2081">使用一个或多个现有列设置DataFrame索引（行标签）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2082"><a class="reference internal" href="generated/pandas.DataFrame.tail.html#pandas.DataFrame.tail" title="pandas.DataFrame.tail"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.tail</span></code></a>（[n]）</span></td>
<td><span class="yiyi-st" id="yiyi-2083">返回最后n行</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2084"><a class="reference internal" href="generated/pandas.DataFrame.take.html#pandas.DataFrame.take" title="pandas.DataFrame.take"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.take</span></code></a>（indices [，axis，convert，is_copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-2085">类似于ndarray.take</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2086"><a class="reference internal" href="generated/pandas.DataFrame.truncate.html#pandas.DataFrame.truncate" title="pandas.DataFrame.truncate"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.truncate</span></code></a>（[before，after，axis，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-2087">在某个特定索引值之前和/或之后截断排序的NDFrame。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="api-dataframe-missing">
<span id="id8"></span><h3><span class="yiyi-st" id="yiyi-2088">缺少数据处理</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2089"><a class="reference internal" href="generated/pandas.DataFrame.dropna.html#pandas.DataFrame.dropna" title="pandas.DataFrame.dropna"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.dropna</span></code></a>（[axis，how，thresh，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2090">返回具有给定轴上的标签的对象在哪里交替地被省略</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2091"><a class="reference internal" href="generated/pandas.DataFrame.fillna.html#pandas.DataFrame.fillna" title="pandas.DataFrame.fillna"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.fillna</span></code></a>（[value，method，axis，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2092">使用指定的方法填充NA / NaN值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2093"><a class="reference internal" href="generated/pandas.DataFrame.replace.html#pandas.DataFrame.replace" title="pandas.DataFrame.replace"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.replace</span></code></a>（[to_replace，value，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2094">将&apos;to_replace&apos;中给出的值替换为&apos;value&apos;。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="reshaping-sorting-transposing">
<h3><span class="yiyi-st" id="yiyi-2095">重新整形，排序，转置</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2096"><a class="reference internal" href="generated/pandas.DataFrame.pivot.html#pandas.DataFrame.pivot" title="pandas.DataFrame.pivot"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.pivot</span></code></a>（[index，columns，values]）</span></td>
<td><span class="yiyi-st" id="yiyi-2097">基于列值重塑数据（生成“枢轴”表）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2098"><a class="reference internal" href="generated/pandas.DataFrame.reorder_levels.html#pandas.DataFrame.reorder_levels" title="pandas.DataFrame.reorder_levels"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.reorder_levels</span></code></a>（order [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2099">使用输入顺序重新排列索引级别。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2100"><a class="reference internal" href="generated/pandas.DataFrame.sort_values.html#pandas.DataFrame.sort_values" title="pandas.DataFrame.sort_values"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.sort_values</span></code></a>（由[，axis，ascending，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2101">按任一轴的值排序</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2102"><a class="reference internal" href="generated/pandas.DataFrame.sort_index.html#pandas.DataFrame.sort_index" title="pandas.DataFrame.sort_index"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.sort_index</span></code></a>（[axis，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2103">按标签（沿轴）对对象排序</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2104"><a class="reference internal" href="generated/pandas.DataFrame.sortlevel.html#pandas.DataFrame.sortlevel" title="pandas.DataFrame.sortlevel"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.sortlevel</span></code></a>（[level，axis，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2105">按所选轴和主要级别对多级索引进行排序。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2106"><a class="reference internal" href="generated/pandas.DataFrame.nlargest.html#pandas.DataFrame.nlargest" title="pandas.DataFrame.nlargest"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.nlargest</span></code></a>（n，columns [，keep]）</span></td>
<td><span class="yiyi-st" id="yiyi-2107">获取按<cite>列</cite>的<cite>n</cite>最大值排序的DataFrame的行。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2108"><a class="reference internal" href="generated/pandas.DataFrame.nsmallest.html#pandas.DataFrame.nsmallest" title="pandas.DataFrame.nsmallest"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.nsmallest</span></code></a>（n，columns [，keep]）</span></td>
<td><span class="yiyi-st" id="yiyi-2109">获取按<cite>列</cite>的<cite>n</cite>最小值排序的DataFrame的行。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2110"><a class="reference internal" href="generated/pandas.DataFrame.swaplevel.html#pandas.DataFrame.swaplevel" title="pandas.DataFrame.swaplevel"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.swaplevel</span></code></a>（[i，j，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2111">在特定轴上的多索引中交换级别i和j</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2112"><a class="reference internal" href="generated/pandas.DataFrame.stack.html#pandas.DataFrame.stack" title="pandas.DataFrame.stack"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.stack</span></code></a>（[level，dropna]）</span></td>
<td><span class="yiyi-st" id="yiyi-2113">透视（可能是层次化的）列标签的级别，返回具有层次索引和新的最内层行标签的DataFrame（或者在具有单个列标签的对象的情况下为Series）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2114"><a class="reference internal" href="generated/pandas.DataFrame.unstack.html#pandas.DataFrame.unstack" title="pandas.DataFrame.unstack"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.unstack</span></code></a>（[level，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-2115">透视（必要为分层）索引标签的级别，返回具有新级别列标签的DataFrame，其中最内层级由枢轴索引标签组成。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2116"><a class="reference internal" href="generated/pandas.DataFrame.T.html#pandas.DataFrame.T" title="pandas.DataFrame.T"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.T</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2117">转置索引和列</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2118"><a class="reference internal" href="generated/pandas.DataFrame.to_panel.html#pandas.DataFrame.to_panel" title="pandas.DataFrame.to_panel"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_panel</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2119">将长（堆叠）格式（DataFrame）转换为宽（3D，面板）格式。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2120"><a class="reference internal" href="generated/pandas.DataFrame.to_xarray.html#pandas.DataFrame.to_xarray" title="pandas.DataFrame.to_xarray"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_xarray</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2121">从pandas对象返回一个xarray对象。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2122"><a class="reference internal" href="generated/pandas.DataFrame.transpose.html#pandas.DataFrame.transpose" title="pandas.DataFrame.transpose"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.transpose</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2123">转置索引和列</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id9">
<h3><span class="yiyi-st" id="yiyi-2124">组合/加入/合并</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2125"><a class="reference internal" href="generated/pandas.DataFrame.append.html#pandas.DataFrame.append" title="pandas.DataFrame.append"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.append</span></code></a>（other [，ignore_index，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2126">将<cite>其他</cite>的行追加到此框架的结尾，返回一个新对象。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2127"><a class="reference internal" href="generated/pandas.DataFrame.assign.html#pandas.DataFrame.assign" title="pandas.DataFrame.assign"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.assign</span></code></a>（\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2128">将新列分配给DataFrame，返回除了新对象之外的所有原始列的新对象（副本）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2129"><a class="reference internal" href="generated/pandas.DataFrame.join.html#pandas.DataFrame.join" title="pandas.DataFrame.join"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.join</span></code></a>（other [，on，how，lsuffix，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2130">与索引或键列上的其他DataFrame连接列。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2131"><a class="reference internal" href="generated/pandas.DataFrame.merge.html#pandas.DataFrame.merge" title="pandas.DataFrame.merge"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.merge</span></code></a>（右[，how，on，left_on，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2132">通过按列或索引执行数据库样式的连接操作来合并DataFrame对象。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2133"><a class="reference internal" href="generated/pandas.DataFrame.update.html#pandas.DataFrame.update" title="pandas.DataFrame.update"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.update</span></code></a>（其他[，join，overwrite，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2134">使用来自传递的DataFrame的非NA值修改DataFrame。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id10">
<h3><span class="yiyi-st" id="yiyi-2135">时间序列相关的</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2136"><a class="reference internal" href="generated/pandas.DataFrame.asfreq.html#pandas.DataFrame.asfreq" title="pandas.DataFrame.asfreq"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.asfreq</span></code></a>（freq [，method，how，normalize]）</span></td>
<td><span class="yiyi-st" id="yiyi-2137">将TimeSeries转换为指定的频率。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2138"><a class="reference internal" href="generated/pandas.DataFrame.asof.html#pandas.DataFrame.asof" title="pandas.DataFrame.asof"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.asof</span></code></a>（其中[，subset]）</span></td>
<td><span class="yiyi-st" id="yiyi-2139">最后一行没有任何NaN被采取（或最后一行没有</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2140"><a class="reference internal" href="generated/pandas.DataFrame.shift.html#pandas.DataFrame.shift" title="pandas.DataFrame.shift"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.shift</span></code></a>（[periods，freq，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2141">使用可选的时间频率按期望的周期数切换索引</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2142"><a class="reference internal" href="generated/pandas.DataFrame.first_valid_index.html#pandas.DataFrame.first_valid_index" title="pandas.DataFrame.first_valid_index"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.first_valid_index</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2143">返回第一个非NA /空值的标签</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2144"><a class="reference internal" href="generated/pandas.DataFrame.last_valid_index.html#pandas.DataFrame.last_valid_index" title="pandas.DataFrame.last_valid_index"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.last_valid_index</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2145">返回最后一个非NA /空值的标签</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2146"><a class="reference internal" href="generated/pandas.DataFrame.resample.html#pandas.DataFrame.resample" title="pandas.DataFrame.resample"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.resample</span></code></a>（rule [，how，axis，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2147">时间序列的频率转换和重采样的方便方法。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2148"><a class="reference internal" href="generated/pandas.DataFrame.to_period.html#pandas.DataFrame.to_period" title="pandas.DataFrame.to_period"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_period</span></code></a>（[freq，axis，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-2149">将DataFrame从DatetimeIndex转换为期间索引</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2150"><a class="reference internal" href="generated/pandas.DataFrame.to_timestamp.html#pandas.DataFrame.to_timestamp" title="pandas.DataFrame.to_timestamp"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_timestamp</span></code></a>（[freq，how，axis，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-2151">在期间的<em>开始</em>，投放到时间戳的DatetimeIndex</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2152"><a class="reference internal" href="generated/pandas.DataFrame.tz_convert.html#pandas.DataFrame.tz_convert" title="pandas.DataFrame.tz_convert"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.tz_convert</span></code></a>（tz [，axis，level，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-2153">将tz感知轴转换为目标时区。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2154"><a class="reference internal" href="generated/pandas.DataFrame.tz_localize.html#pandas.DataFrame.tz_localize" title="pandas.DataFrame.tz_localize"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.tz_localize</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2155">将tz-naive TimeSeries本地化为目标时区。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="api-dataframe-plotting">
<span id="id11"></span><h3><span class="yiyi-st" id="yiyi-2156">绘制</span></h3>
<p><span class="yiyi-st" id="yiyi-2157"><code class="docutils literal"><span class="pre">DataFrame.plot</span></code>是用于<code class="docutils literal"><span class="pre">DataFrame.plot.&lt;kind&gt;</span></code>形式的特定绘图方法的可调用方法和命名空间属性。</span></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2158"><a class="reference internal" href="generated/pandas.DataFrame.plot.html#pandas.DataFrame.plot" title="pandas.DataFrame.plot"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.plot</span></code></a>（[x，y，kind，ax，....]）</span></td>
<td><span class="yiyi-st" id="yiyi-2159">DataFrame绘制访问器和方法</span></td>
</tr>
</tbody>
</table>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2160"><a class="reference internal" href="generated/pandas.DataFrame.plot.area.html#pandas.DataFrame.plot.area" title="pandas.DataFrame.plot.area"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.plot.area</span></code></a>（[x，y]）</span></td>
<td><span class="yiyi-st" id="yiyi-2161">面积图</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2162"><a class="reference internal" href="generated/pandas.DataFrame.plot.bar.html#pandas.DataFrame.plot.bar" title="pandas.DataFrame.plot.bar"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.plot.bar</span></code></a>（[x，y]）</span></td>
<td><span class="yiyi-st" id="yiyi-2163">垂直条图</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2164"><a class="reference internal" href="generated/pandas.DataFrame.plot.barh.html#pandas.DataFrame.plot.barh" title="pandas.DataFrame.plot.barh"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.plot.barh</span></code></a>（[x，y]）</span></td>
<td><span class="yiyi-st" id="yiyi-2165">水平条图</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2166"><a class="reference internal" href="generated/pandas.DataFrame.plot.box.html#pandas.DataFrame.plot.box" title="pandas.DataFrame.plot.box"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.plot.box</span></code></a>（[by]）</span></td>
<td><span class="yiyi-st" id="yiyi-2167">箱形图</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2168"><a class="reference internal" href="generated/pandas.DataFrame.plot.density.html#pandas.DataFrame.plot.density" title="pandas.DataFrame.plot.density"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.plot.density</span></code></a>（\ * \ * kwds）</span></td>
<td><span class="yiyi-st" id="yiyi-2169">核密度估计图</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2170"><a class="reference internal" href="generated/pandas.DataFrame.plot.hexbin.html#pandas.DataFrame.plot.hexbin" title="pandas.DataFrame.plot.hexbin"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.plot.hexbin</span></code></a>（x，y [，C，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2171">Hexbin图</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2172"><a class="reference internal" href="generated/pandas.DataFrame.plot.hist.html#pandas.DataFrame.plot.hist" title="pandas.DataFrame.plot.hist"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.plot.hist</span></code></a>（[by，bins]）</span></td>
<td><span class="yiyi-st" id="yiyi-2173">直方图</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2174"><a class="reference internal" href="generated/pandas.DataFrame.plot.kde.html#pandas.DataFrame.plot.kde" title="pandas.DataFrame.plot.kde"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.plot.kde</span></code></a>（\ * \ * kwds）</span></td>
<td><span class="yiyi-st" id="yiyi-2175">核密度估计图</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2176"><a class="reference internal" href="generated/pandas.DataFrame.plot.line.html#pandas.DataFrame.plot.line" title="pandas.DataFrame.plot.line"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.plot.line</span></code></a>（[x，y]）</span></td>
<td><span class="yiyi-st" id="yiyi-2177">线图</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2178"><a class="reference internal" href="generated/pandas.DataFrame.plot.pie.html#pandas.DataFrame.plot.pie" title="pandas.DataFrame.plot.pie"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.plot.pie</span></code></a>（[y]）</span></td>
<td><span class="yiyi-st" id="yiyi-2179">饼形图</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2180"><a class="reference internal" href="generated/pandas.DataFrame.plot.scatter.html#pandas.DataFrame.plot.scatter" title="pandas.DataFrame.plot.scatter"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.plot.scatter</span></code></a>（x，y [，s，c]）</span></td>
<td><span class="yiyi-st" id="yiyi-2181">散点图</span></td>
</tr>
</tbody>
</table>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2182"><a class="reference internal" href="generated/pandas.DataFrame.boxplot.html#pandas.DataFrame.boxplot" title="pandas.DataFrame.boxplot"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.boxplot</span></code></a>（[column，by，ax，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2183">从DataFrame列创建箱绘图，可选择按一些列或分组</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2184"><a class="reference internal" href="generated/pandas.DataFrame.hist.html#pandas.DataFrame.hist" title="pandas.DataFrame.hist"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.hist</span></code></a>（data [，column，by，grid，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2185">使用matplotlib / pylab绘制DataFrame系列的直方图。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id12">
<h3><span class="yiyi-st" id="yiyi-2186">序列化/ IO /转换</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2187"><a class="reference internal" href="generated/pandas.DataFrame.from_csv.html#pandas.DataFrame.from_csv" title="pandas.DataFrame.from_csv"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.from_csv</span></code></a>（path [，header，sep，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2188">读取CSV文件（DISCOURAGED，请改用<a class="reference internal" href="generated/pandas.read_csv.html#pandas.read_csv" title="pandas.read_csv"><code class="xref py py-func docutils literal"><span class="pre">pandas.read_csv()</span></code></a>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2189"><a class="reference internal" href="generated/pandas.DataFrame.from_dict.html#pandas.DataFrame.from_dict" title="pandas.DataFrame.from_dict"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.from_dict</span></code></a>（data [，orient，dtype]）</span></td>
<td><span class="yiyi-st" id="yiyi-2190">从类array或dicts的dict构造DataFrame</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2191"><a class="reference internal" href="generated/pandas.DataFrame.from_items.html#pandas.DataFrame.from_items" title="pandas.DataFrame.from_items"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.from_items</span></code></a>（items [，columns，orient]）</span></td>
<td><span class="yiyi-st" id="yiyi-2192">将（键，值）对转换为DataFrame。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2193"><a class="reference internal" href="generated/pandas.DataFrame.from_records.html#pandas.DataFrame.from_records" title="pandas.DataFrame.from_records"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.from_records</span></code></a>（data [，index，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2194">将结构化或记录ndarray转换为DataFrame</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2195"><a class="reference internal" href="generated/pandas.DataFrame.info.html#pandas.DataFrame.info" title="pandas.DataFrame.info"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.info</span></code></a>（[verbose，buf，max_cols，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2196">DataFrame的简明摘要。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2197"><a class="reference internal" href="generated/pandas.DataFrame.to_pickle.html#pandas.DataFrame.to_pickle" title="pandas.DataFrame.to_pickle"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_pickle</span></code></a>（path）</span></td>
<td><span class="yiyi-st" id="yiyi-2198">Pickle（序列化）对象到输入文件路径。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2199"><a class="reference internal" href="generated/pandas.DataFrame.to_csv.html#pandas.DataFrame.to_csv" title="pandas.DataFrame.to_csv"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_csv</span></code></a>（[path_or_buf，sep，na_rep，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2200">将DataFrame写入逗号分隔值（csv）文件</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2201"><a class="reference internal" href="generated/pandas.DataFrame.to_hdf.html#pandas.DataFrame.to_hdf" title="pandas.DataFrame.to_hdf"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_hdf</span></code></a>（path_or_buf，key，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2202">使用HDFStore将包含的数据写入HDF5文件。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2203"><a class="reference internal" href="generated/pandas.DataFrame.to_sql.html#pandas.DataFrame.to_sql" title="pandas.DataFrame.to_sql"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_sql</span></code></a>（name，con [，flavor，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2204">将存储在DataFrame中的记录写入SQL数据库。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2205"><a class="reference internal" href="generated/pandas.DataFrame.to_dict.html#pandas.DataFrame.to_dict" title="pandas.DataFrame.to_dict"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_dict</span></code></a>（[orient]）</span></td>
<td><span class="yiyi-st" id="yiyi-2206">将DataFrame转换成字典。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2207"><a class="reference internal" href="generated/pandas.DataFrame.to_excel.html#pandas.DataFrame.to_excel" title="pandas.DataFrame.to_excel"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_excel</span></code></a>（excel_writer [，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2208">将DataFrame写入excel表</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2209"><a class="reference internal" href="generated/pandas.DataFrame.to_json.html#pandas.DataFrame.to_json" title="pandas.DataFrame.to_json"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_json</span></code></a>（[path_or_buf，orient，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2210">将对象转换为JSON字符串。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2211"><a class="reference internal" href="generated/pandas.DataFrame.to_html.html#pandas.DataFrame.to_html" title="pandas.DataFrame.to_html"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_html</span></code></a>（[buf，columns，col_space，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2212">将DataFrame呈现为HTML表格。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2213"><a class="reference internal" href="generated/pandas.DataFrame.to_latex.html#pandas.DataFrame.to_latex" title="pandas.DataFrame.to_latex"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_latex</span></code></a>（[buf，columns，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2214">将DataFrame呈现为表格环境表。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2215"><a class="reference internal" href="generated/pandas.DataFrame.to_stata.html#pandas.DataFrame.to_stata" title="pandas.DataFrame.to_stata"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_stata</span></code></a>（fname [，convert_dates，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2216">从数组类对象中写入Stata二进制dta文件的类</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2217"><a class="reference internal" href="generated/pandas.DataFrame.to_msgpack.html#pandas.DataFrame.to_msgpack" title="pandas.DataFrame.to_msgpack"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_msgpack</span></code></a>（[path_or_buf，encoding]）</span></td>
<td><span class="yiyi-st" id="yiyi-2218">msgpack（serialize）对象到输入文件路径</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2219"><a class="reference internal" href="generated/pandas.DataFrame.to_gbq.html#pandas.DataFrame.to_gbq" title="pandas.DataFrame.to_gbq"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_gbq</span></code></a>（destination_table，project_id）</span></td>
<td><span class="yiyi-st" id="yiyi-2220">将DataFrame写入Google BigQuery表格。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2221"><a class="reference internal" href="generated/pandas.DataFrame.to_records.html#pandas.DataFrame.to_records" title="pandas.DataFrame.to_records"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_records</span></code></a>（[index，convert_datetime64]）</span></td>
<td><span class="yiyi-st" id="yiyi-2222">将DataFrame转换为记录数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2223"><a class="reference internal" href="generated/pandas.DataFrame.to_sparse.html#pandas.DataFrame.to_sparse" title="pandas.DataFrame.to_sparse"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_sparse</span></code></a>（[fill_value，kind]）</span></td>
<td><span class="yiyi-st" id="yiyi-2224">转换为SparseDataFrame</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2225"><a class="reference internal" href="generated/pandas.DataFrame.to_dense.html#pandas.DataFrame.to_dense" title="pandas.DataFrame.to_dense"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_dense</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2226">返回NDFrame的密集表示（而不是稀疏）</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2227"><a class="reference internal" href="generated/pandas.DataFrame.to_string.html#pandas.DataFrame.to_string" title="pandas.DataFrame.to_string"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_string</span></code></a>（[buf，columns，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2228">将DataFrame呈现为控制台友好的表格输出。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2229"><a class="reference internal" href="generated/pandas.DataFrame.to_clipboard.html#pandas.DataFrame.to_clipboard" title="pandas.DataFrame.to_clipboard"><code class="xref py py-obj docutils literal"><span class="pre">DataFrame.to_clipboard</span></code></a>（[excel，sep]）</span></td>
<td><span class="yiyi-st" id="yiyi-2230">尝试将对象的文本表示写入系统剪贴板例如，可以将其粘贴到Excel中。</span></td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section" id="panel">
<span id="api-panel"></span><h2><span class="yiyi-st" id="yiyi-2231">面板</span></h2>
<div class="section" id="id13">
<h3><span class="yiyi-st" id="yiyi-2232">构造</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2233"><a class="reference internal" href="generated/pandas.Panel.html#pandas.Panel" title="pandas.Panel"><code class="xref py py-obj docutils literal"><span class="pre">Panel</span></code></a>（[data，items，major_axis，minor_axis，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2234">表示宽格式面板数据，存储为3维数组</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id14">
<h3><span class="yiyi-st" id="yiyi-2235">属性和底层数据</span></h3>
<p><span class="yiyi-st" id="yiyi-2236"><strong>轴</strong></span></p>
<blockquote>
<div><ul class="simple">
<li><span class="yiyi-st" id="yiyi-2237"><strong>项</strong>：axis 0；每个项目对应于其中包含的DataFrame</span></li>
<li><span class="yiyi-st" id="yiyi-2238"><strong>major_axis</strong>：轴1；每个DataFrames的索引（行）</span></li>
<li><span class="yiyi-st" id="yiyi-2239"><strong>minor_axis</strong>：axis 2；每个DataFrames的列</span></li>
</ul>
</div></blockquote>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2240"><a class="reference internal" href="generated/pandas.Panel.values.html#pandas.Panel.values" title="pandas.Panel.values"><code class="xref py py-obj docutils literal"><span class="pre">Panel.values</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2241">NDFrame的块状表示</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2242"><a class="reference internal" href="generated/pandas.Panel.axes.html#pandas.Panel.axes" title="pandas.Panel.axes"><code class="xref py py-obj docutils literal"><span class="pre">Panel.axes</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2243">返回内部NDFrame的索引标签</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2244"><a class="reference internal" href="generated/pandas.Panel.ndim.html#pandas.Panel.ndim" title="pandas.Panel.ndim"><code class="xref py py-obj docutils literal"><span class="pre">Panel.ndim</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2245">轴数/阵列尺寸</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2246"><a class="reference internal" href="generated/pandas.Panel.size.html#pandas.Panel.size" title="pandas.Panel.size"><code class="xref py py-obj docutils literal"><span class="pre">Panel.size</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2247">NDFrame中的元素数</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2248"><a class="reference internal" href="generated/pandas.Panel.shape.html#pandas.Panel.shape" title="pandas.Panel.shape"><code class="xref py py-obj docutils literal"><span class="pre">Panel.shape</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2249">返回轴维度的元组</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2250"><a class="reference internal" href="generated/pandas.Panel.dtypes.html#pandas.Panel.dtypes" title="pandas.Panel.dtypes"><code class="xref py py-obj docutils literal"><span class="pre">Panel.dtypes</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2251">返回此对象中的dtype。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2252"><a class="reference internal" href="generated/pandas.Panel.ftypes.html#pandas.Panel.ftypes" title="pandas.Panel.ftypes"><code class="xref py py-obj docutils literal"><span class="pre">Panel.ftypes</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2253">返回此对象中的ftypes（稀疏/密集和dtype的指示）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2254"><a class="reference internal" href="generated/pandas.Panel.get_dtype_counts.html#pandas.Panel.get_dtype_counts" title="pandas.Panel.get_dtype_counts"><code class="xref py py-obj docutils literal"><span class="pre">Panel.get_dtype_counts</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2255">返回此对象中的dtypes的计数。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2256"><a class="reference internal" href="generated/pandas.Panel.get_ftype_counts.html#pandas.Panel.get_ftype_counts" title="pandas.Panel.get_ftype_counts"><code class="xref py py-obj docutils literal"><span class="pre">Panel.get_ftype_counts</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2257">返回此对象中的ftypes的计数。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id15">
<h3><span class="yiyi-st" id="yiyi-2258">转换</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2259"><a class="reference internal" href="generated/pandas.Panel.astype.html#pandas.Panel.astype" title="pandas.Panel.astype"><code class="xref py py-obj docutils literal"><span class="pre">Panel.astype</span></code></a>（dtype [，copy，raise_on_error]）</span></td>
<td><span class="yiyi-st" id="yiyi-2260">投射对象以输入numpy.dtype</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2261"><a class="reference internal" href="generated/pandas.Panel.copy.html#pandas.Panel.copy" title="pandas.Panel.copy"><code class="xref py py-obj docutils literal"><span class="pre">Panel.copy</span></code></a>（[deep]）</span></td>
<td><span class="yiyi-st" id="yiyi-2262">复制此对象数据。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2263"><a class="reference internal" href="generated/pandas.Panel.isnull.html#pandas.Panel.isnull" title="pandas.Panel.isnull"><code class="xref py py-obj docutils literal"><span class="pre">Panel.isnull</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2264">返回一个布尔大小相同的对象，指示值是否为null。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2265"><a class="reference internal" href="generated/pandas.Panel.notnull.html#pandas.Panel.notnull" title="pandas.Panel.notnull"><code class="xref py py-obj docutils literal"><span class="pre">Panel.notnull</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2266">返回一个布尔大小相同的对象，指示这些值是否为空。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="getting-and-setting">
<h3><span class="yiyi-st" id="yiyi-2267">获取并设置</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2268"><a class="reference internal" href="generated/pandas.Panel.get_value.html#pandas.Panel.get_value" title="pandas.Panel.get_value"><code class="xref py py-obj docutils literal"><span class="pre">Panel.get_value</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2269">在（项目，主要，次要）位置快速检索单个值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2270"><a class="reference internal" href="generated/pandas.Panel.set_value.html#pandas.Panel.set_value" title="pandas.Panel.set_value"><code class="xref py py-obj docutils literal"><span class="pre">Panel.set_value</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2271">在（项目，主要，次要）位置快速设置单一值</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="indexing-iteration-slicing">
<h3><span class="yiyi-st" id="yiyi-2272">索引，迭代，切片</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2273"><a class="reference internal" href="generated/pandas.Panel.at.html#pandas.Panel.at" title="pandas.Panel.at"><code class="xref py py-obj docutils literal"><span class="pre">Panel.at</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2274">基于快速标签的标量访问器</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2275"><a class="reference internal" href="generated/pandas.Panel.iat.html#pandas.Panel.iat" title="pandas.Panel.iat"><code class="xref py py-obj docutils literal"><span class="pre">Panel.iat</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2276">快速整数位置标量存取器。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2277"><a class="reference internal" href="generated/pandas.Panel.ix.html#pandas.Panel.ix" title="pandas.Panel.ix"><code class="xref py py-obj docutils literal"><span class="pre">Panel.ix</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2278">主要是基于标签位置的索引器，具有整数位置后备。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2279"><a class="reference internal" href="generated/pandas.Panel.loc.html#pandas.Panel.loc" title="pandas.Panel.loc"><code class="xref py py-obj docutils literal"><span class="pre">Panel.loc</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2280">纯标签位置索引器，用于按标签选择。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2281"><a class="reference internal" href="generated/pandas.Panel.iloc.html#pandas.Panel.iloc" title="pandas.Panel.iloc"><code class="xref py py-obj docutils literal"><span class="pre">Panel.iloc</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2282">纯粹基于整数位置的索引，用于按位置选择。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2283"><a class="reference internal" href="generated/pandas.Panel.__iter__.html#pandas.Panel.__iter__" title="pandas.Panel.__iter__"><code class="xref py py-obj docutils literal"><span class="pre">Panel.__iter__</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2284">在信息轴上迭代</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2285"><a class="reference internal" href="generated/pandas.Panel.iteritems.html#pandas.Panel.iteritems" title="pandas.Panel.iteritems"><code class="xref py py-obj docutils literal"><span class="pre">Panel.iteritems</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2286">在信息轴上迭代（标签，值）</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2287"><a class="reference internal" href="generated/pandas.Panel.pop.html#pandas.Panel.pop" title="pandas.Panel.pop"><code class="xref py py-obj docutils literal"><span class="pre">Panel.pop</span></code></a>（item）</span></td>
<td><span class="yiyi-st" id="yiyi-2288">返回项目并从框架中删除。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2289"><a class="reference internal" href="generated/pandas.Panel.xs.html#pandas.Panel.xs" title="pandas.Panel.xs"><code class="xref py py-obj docutils literal"><span class="pre">Panel.xs</span></code></a>（键[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2290">沿所选轴返回面板</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2291"><a class="reference internal" href="generated/pandas.Panel.major_xs.html#pandas.Panel.major_xs" title="pandas.Panel.major_xs"><code class="xref py py-obj docutils literal"><span class="pre">Panel.major_xs</span></code></a>（key）</span></td>
<td><span class="yiyi-st" id="yiyi-2292">面板沿主轴返回切片</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2293"><a class="reference internal" href="generated/pandas.Panel.minor_xs.html#pandas.Panel.minor_xs" title="pandas.Panel.minor_xs"><code class="xref py py-obj docutils literal"><span class="pre">Panel.minor_xs</span></code></a>（key）</span></td>
<td><span class="yiyi-st" id="yiyi-2294">沿着短轴返回面板</span></td>
</tr>
</tbody>
</table>
<p><span class="yiyi-st" id="yiyi-2295">有关<code class="docutils literal"><span class="pre">.at</span></code>，<code class="docutils literal"><span class="pre">.iat</span></code>，<code class="docutils literal"><span class="pre">.ix</span></code>，<code class="docutils literal"><span class="pre">.loc</span></code>和<code class="docutils literal"><span class="pre">.iloc</span></code>，请参阅<a class="reference internal" href="indexing.html#indexing"><span class="std std-ref">indexing documentation</span></a>。</span></p>
</div>
<div class="section" id="id16">
<h3><span class="yiyi-st" id="yiyi-2296">二进制运算符函数</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2297"><a class="reference internal" href="generated/pandas.Panel.add.html#pandas.Panel.add" title="pandas.Panel.add"><code class="xref py py-obj docutils literal"><span class="pre">Panel.add</span></code></a>（其他[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2298">添加系列和其他，元素方式（二元运算符<cite>add</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2299"><a class="reference internal" href="generated/pandas.Panel.sub.html#pandas.Panel.sub" title="pandas.Panel.sub"><code class="xref py py-obj docutils literal"><span class="pre">Panel.sub</span></code></a>（其他[，轴]）</span></td>
<td><span class="yiyi-st" id="yiyi-2300">减法系数和其他，元素方式（二元运算符<cite>子</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2301"><a class="reference internal" href="generated/pandas.Panel.mul.html#pandas.Panel.mul" title="pandas.Panel.mul"><code class="xref py py-obj docutils literal"><span class="pre">Panel.mul</span></code></a>（其他[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2302">系列和其他元素乘法（二元算符<cite>mul</cite>）的乘法。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2303"><a class="reference internal" href="generated/pandas.Panel.div.html#pandas.Panel.div" title="pandas.Panel.div"><code class="xref py py-obj docutils literal"><span class="pre">Panel.div</span></code></a>（其他[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2304">浮点除法的系列和其他，元素（二进制运算符<cite>truediv</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2305"><a class="reference internal" href="generated/pandas.Panel.truediv.html#pandas.Panel.truediv" title="pandas.Panel.truediv"><code class="xref py py-obj docutils literal"><span class="pre">Panel.truediv</span></code></a>（other [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2306">浮点除法的系列和其他，元素（二进制运算符<cite>truediv</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2307"><a class="reference internal" href="generated/pandas.Panel.floordiv.html#pandas.Panel.floordiv" title="pandas.Panel.floordiv"><code class="xref py py-obj docutils literal"><span class="pre">Panel.floordiv</span></code></a>（其他[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2308">系列的整数除法和其他，元素方式（二元运算符<cite>floordiv</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2309"><a class="reference internal" href="generated/pandas.Panel.mod.html#pandas.Panel.mod" title="pandas.Panel.mod"><code class="xref py py-obj docutils literal"><span class="pre">Panel.mod</span></code></a>（其他[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2310">系列模和其他，元素方式（二元运算符<cite>mod</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2311"><a class="reference internal" href="generated/pandas.Panel.pow.html#pandas.Panel.pow" title="pandas.Panel.pow"><code class="xref py py-obj docutils literal"><span class="pre">Panel.pow</span></code></a>（其他[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2312">系数和其他元指数（二元运算符<cite>pow</cite>）的指数幂。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2313"><a class="reference internal" href="generated/pandas.Panel.radd.html#pandas.Panel.radd" title="pandas.Panel.radd"><code class="xref py py-obj docutils literal"><span class="pre">Panel.radd</span></code></a>（其他[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2314">添加系列和其他，元素方式（二元算符<cite>radd</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2315"><a class="reference internal" href="generated/pandas.Panel.rsub.html#pandas.Panel.rsub" title="pandas.Panel.rsub"><code class="xref py py-obj docutils literal"><span class="pre">Panel.rsub</span></code></a>（其他[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2316">减法系列和其他，元素方式（二元运算符<cite>rsub</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2317"><a class="reference internal" href="generated/pandas.Panel.rmul.html#pandas.Panel.rmul" title="pandas.Panel.rmul"><code class="xref py py-obj docutils literal"><span class="pre">Panel.rmul</span></code></a>（其他[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2318">系列和其他元素乘法（二元算符<cite>rmul</cite>）的乘法。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2319"><a class="reference internal" href="generated/pandas.Panel.rdiv.html#pandas.Panel.rdiv" title="pandas.Panel.rdiv"><code class="xref py py-obj docutils literal"><span class="pre">Panel.rdiv</span></code></a>（其他[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2320">浮点除法的系列和其他，元素（二进制运算符<cite>rtruediv</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2321"><a class="reference internal" href="generated/pandas.Panel.rtruediv.html#pandas.Panel.rtruediv" title="pandas.Panel.rtruediv"><code class="xref py py-obj docutils literal"><span class="pre">Panel.rtruediv</span></code></a>（其他[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2322">浮点除法的系列和其他，元素（二进制运算符<cite>rtruediv</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2323"><a class="reference internal" href="generated/pandas.Panel.rfloordiv.html#pandas.Panel.rfloordiv" title="pandas.Panel.rfloordiv"><code class="xref py py-obj docutils literal"><span class="pre">Panel.rfloordiv</span></code></a>（其他[，轴]）</span></td>
<td><span class="yiyi-st" id="yiyi-2324">系列的整数除法和其他，元素方式（二元运算符<cite>rfloordiv</cite>）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2325"><a class="reference internal" href="generated/pandas.Panel.rmod.html#pandas.Panel.rmod" title="pandas.Panel.rmod"><code class="xref py py-obj docutils literal"><span class="pre">Panel.rmod</span></code></a>（其他[，轴]）</span></td>
<td><span class="yiyi-st" id="yiyi-2326">系列模和其他，元素方式（二元算符<cite>rmod</cite>）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2327"><a class="reference internal" href="generated/pandas.Panel.rpow.html#pandas.Panel.rpow" title="pandas.Panel.rpow"><code class="xref py py-obj docutils literal"><span class="pre">Panel.rpow</span></code></a>（其他[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2328">系列和其他元指数（二元运算符<cite>rpow</cite>）的指数幂。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2329"><a class="reference internal" href="generated/pandas.Panel.lt.html#pandas.Panel.lt" title="pandas.Panel.lt"><code class="xref py py-obj docutils literal"><span class="pre">Panel.lt</span></code></a>（其他[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2330">比较方法的包装</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2331"><a class="reference internal" href="generated/pandas.Panel.gt.html#pandas.Panel.gt" title="pandas.Panel.gt"><code class="xref py py-obj docutils literal"><span class="pre">Panel.gt</span></code></a>（其他[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2332">比较方法的包装器gt</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2333"><a class="reference internal" href="generated/pandas.Panel.le.html#pandas.Panel.le" title="pandas.Panel.le"><code class="xref py py-obj docutils literal"><span class="pre">Panel.le</span></code></a>（其他[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2334">比较方法le的包装</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2335"><a class="reference internal" href="generated/pandas.Panel.ge.html#pandas.Panel.ge" title="pandas.Panel.ge"><code class="xref py py-obj docutils literal"><span class="pre">Panel.ge</span></code></a>（其他[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2336">比较方法包装</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2337"><a class="reference internal" href="generated/pandas.Panel.ne.html#pandas.Panel.ne" title="pandas.Panel.ne"><code class="xref py py-obj docutils literal"><span class="pre">Panel.ne</span></code></a>（其他[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2338">比较方法ne</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2339"><a class="reference internal" href="generated/pandas.Panel.eq.html#pandas.Panel.eq" title="pandas.Panel.eq"><code class="xref py py-obj docutils literal"><span class="pre">Panel.eq</span></code></a>（其他[，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2340">比较方法的包装器</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="function-application-groupby">
<h3><span class="yiyi-st" id="yiyi-2341">功能应用程序，GroupBy </span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2342"><a class="reference internal" href="generated/pandas.Panel.apply.html#pandas.Panel.apply" title="pandas.Panel.apply"><code class="xref py py-obj docutils literal"><span class="pre">Panel.apply</span></code></a>（func [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2343">沿面板的轴（或轴）应用功能</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2344"><a class="reference internal" href="generated/pandas.Panel.groupby.html#pandas.Panel.groupby" title="pandas.Panel.groupby"><code class="xref py py-obj docutils literal"><span class="pre">Panel.groupby</span></code></a>（function [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2345">给定轴上的数据组，返回GroupBy对象</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="api-panel-stats">
<span id="id17"></span><h3><span class="yiyi-st" id="yiyi-2346">计算/描述性统计</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2347"><a class="reference internal" href="generated/pandas.Panel.abs.html#pandas.Panel.abs" title="pandas.Panel.abs"><code class="xref py py-obj docutils literal"><span class="pre">Panel.abs</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2348">返回具有绝对值的对象，仅适用于全部为数字的对象。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2349"><a class="reference internal" href="generated/pandas.Panel.clip.html#pandas.Panel.clip" title="pandas.Panel.clip"><code class="xref py py-obj docutils literal"><span class="pre">Panel.clip</span></code></a>（[下，上，轴]）</span></td>
<td><span class="yiyi-st" id="yiyi-2350">修整输入阈值处的值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2351"><a class="reference internal" href="generated/pandas.Panel.clip_lower.html#pandas.Panel.clip_lower" title="pandas.Panel.clip_lower"><code class="xref py py-obj docutils literal"><span class="pre">Panel.clip_lower</span></code></a>（threshold [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2352">返回具有低于给定值的值的输入的副本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2353"><a class="reference internal" href="generated/pandas.Panel.clip_upper.html#pandas.Panel.clip_upper" title="pandas.Panel.clip_upper"><code class="xref py py-obj docutils literal"><span class="pre">Panel.clip_upper</span></code></a>（threshold [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2354">返回具有高于给定值的值的输入的副本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2355"><a class="reference internal" href="generated/pandas.Panel.count.html#pandas.Panel.count" title="pandas.Panel.count"><code class="xref py py-obj docutils literal"><span class="pre">Panel.count</span></code></a>（[axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2356">通过请求的轴返回观测值数。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2357"><a class="reference internal" href="generated/pandas.Panel.cummax.html#pandas.Panel.cummax" title="pandas.Panel.cummax"><code class="xref py py-obj docutils literal"><span class="pre">Panel.cummax</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-2358">返回请求轴上的累积最大值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2359"><a class="reference internal" href="generated/pandas.Panel.cummin.html#pandas.Panel.cummin" title="pandas.Panel.cummin"><code class="xref py py-obj docutils literal"><span class="pre">Panel.cummin</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-2360">返回所请求轴上的累积最小值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2361"><a class="reference internal" href="generated/pandas.Panel.cumprod.html#pandas.Panel.cumprod" title="pandas.Panel.cumprod"><code class="xref py py-obj docutils literal"><span class="pre">Panel.cumprod</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-2362">通过请求轴返回累积乘积。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2363"><a class="reference internal" href="generated/pandas.Panel.cumsum.html#pandas.Panel.cumsum" title="pandas.Panel.cumsum"><code class="xref py py-obj docutils literal"><span class="pre">Panel.cumsum</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-2364">通过请求轴返回累积和。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2365"><a class="reference internal" href="generated/pandas.Panel.max.html#pandas.Panel.max" title="pandas.Panel.max"><code class="xref py py-obj docutils literal"><span class="pre">Panel.max</span></code></a>（[axis，skipna，level，numeric_only]）</span></td>
<td><span class="yiyi-st" id="yiyi-2366">此方法返回对象中值的最大值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2367"><a class="reference internal" href="generated/pandas.Panel.mean.html#pandas.Panel.mean" title="pandas.Panel.mean"><code class="xref py py-obj docutils literal"><span class="pre">Panel.mean</span></code></a>（[axis，skipna，level，numeric_only]）</span></td>
<td><span class="yiyi-st" id="yiyi-2368">返回请求轴的值的平均值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2369"><a class="reference internal" href="generated/pandas.Panel.median.html#pandas.Panel.median" title="pandas.Panel.median"><code class="xref py py-obj docutils literal"><span class="pre">Panel.median</span></code></a>（[axis，skipna，level，numeric_only]）</span></td>
<td><span class="yiyi-st" id="yiyi-2370">返回请求轴的值的中值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2371"><a class="reference internal" href="generated/pandas.Panel.min.html#pandas.Panel.min" title="pandas.Panel.min"><code class="xref py py-obj docutils literal"><span class="pre">Panel.min</span></code></a>（[axis，skipna，level，numeric_only]）</span></td>
<td><span class="yiyi-st" id="yiyi-2372">此方法返回对象中值的最小值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2373"><a class="reference internal" href="generated/pandas.Panel.pct_change.html#pandas.Panel.pct_change" title="pandas.Panel.pct_change"><code class="xref py py-obj docutils literal"><span class="pre">Panel.pct_change</span></code></a>（[periods，fill_method，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2374">给定周期数的百分比变化。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2375"><a class="reference internal" href="generated/pandas.Panel.prod.html#pandas.Panel.prod" title="pandas.Panel.prod"><code class="xref py py-obj docutils literal"><span class="pre">Panel.prod</span></code></a>（[axis，skipna，level，numeric_only]）</span></td>
<td><span class="yiyi-st" id="yiyi-2376">返回请求轴的值的乘积</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2377"><a class="reference internal" href="generated/pandas.Panel.sem.html#pandas.Panel.sem" title="pandas.Panel.sem"><code class="xref py py-obj docutils literal"><span class="pre">Panel.sem</span></code></a>（[axis，skipna，level，ddof，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2378">返回所要求轴的平均值的无偏差标准误差。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2379"><a class="reference internal" href="generated/pandas.Panel.skew.html#pandas.Panel.skew" title="pandas.Panel.skew"><code class="xref py py-obj docutils literal"><span class="pre">Panel.skew</span></code></a>（[axis，skipna，level，numerical_only]）</span></td>
<td><span class="yiyi-st" id="yiyi-2380">返回所请求轴的无偏斜</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2381"><a class="reference internal" href="generated/pandas.Panel.sum.html#pandas.Panel.sum" title="pandas.Panel.sum"><code class="xref py py-obj docutils literal"><span class="pre">Panel.sum</span></code></a>（[axis，skipna，level，numeric_only]）</span></td>
<td><span class="yiyi-st" id="yiyi-2382">返回请求轴的值的总和</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2383"><a class="reference internal" href="generated/pandas.Panel.std.html#pandas.Panel.std" title="pandas.Panel.std"><code class="xref py py-obj docutils literal"><span class="pre">Panel.std</span></code></a>（[axis，skipna，level，ddof，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2384">返回样品标准偏差超过请求的轴。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2385"><a class="reference internal" href="generated/pandas.Panel.var.html#pandas.Panel.var" title="pandas.Panel.var"><code class="xref py py-obj docutils literal"><span class="pre">Panel.var</span></code></a>（[axis，skipna，level，ddof，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2386">返回与请求轴无关的方差。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id18">
<h3><span class="yiyi-st" id="yiyi-2387">重新索引/选择/标签操作</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2388"><a class="reference internal" href="generated/pandas.Panel.add_prefix.html#pandas.Panel.add_prefix" title="pandas.Panel.add_prefix"><code class="xref py py-obj docutils literal"><span class="pre">Panel.add_prefix</span></code></a>（prefix）</span></td>
<td><span class="yiyi-st" id="yiyi-2389">将前缀字符串与面板项名称连接。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2390"><a class="reference internal" href="generated/pandas.Panel.add_suffix.html#pandas.Panel.add_suffix" title="pandas.Panel.add_suffix"><code class="xref py py-obj docutils literal"><span class="pre">Panel.add_suffix</span></code></a>（suffix）</span></td>
<td><span class="yiyi-st" id="yiyi-2391">将后缀字符串与面板项名称连接。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2392"><a class="reference internal" href="generated/pandas.Panel.drop.html#pandas.Panel.drop" title="pandas.Panel.drop"><code class="xref py py-obj docutils literal"><span class="pre">Panel.drop</span></code></a>（标签[，axis，level，inplace，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2393">返回请求轴中标签已删除的新对象。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2394"><a class="reference internal" href="generated/pandas.Panel.equals.html#pandas.Panel.equals" title="pandas.Panel.equals"><code class="xref py py-obj docutils literal"><span class="pre">Panel.equals</span></code></a>（other）</span></td>
<td><span class="yiyi-st" id="yiyi-2395">确定两个NDFrame对象是否包含相同的元素。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2396"><a class="reference internal" href="generated/pandas.Panel.filter.html#pandas.Panel.filter" title="pandas.Panel.filter"><code class="xref py py-obj docutils literal"><span class="pre">Panel.filter</span></code></a>（[items，like，regex，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2397">子集根据指定索引中的标签的数据帧的行或列。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2398"><a class="reference internal" href="generated/pandas.Panel.first.html#pandas.Panel.first" title="pandas.Panel.first"><code class="xref py py-obj docutils literal"><span class="pre">Panel.first</span></code></a>（偏移）</span></td>
<td><span class="yiyi-st" id="yiyi-2399">用于基于日期偏移对时间序列数据的初始时间进行子集化的便利方法。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2400"><a class="reference internal" href="generated/pandas.Panel.last.html#pandas.Panel.last" title="pandas.Panel.last"><code class="xref py py-obj docutils literal"><span class="pre">Panel.last</span></code></a>（offset）</span></td>
<td><span class="yiyi-st" id="yiyi-2401">基于日期偏移对时间序列数据的最终周期进行子集化的便利方法。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2402"><a class="reference internal" href="generated/pandas.Panel.reindex.html#pandas.Panel.reindex" title="pandas.Panel.reindex"><code class="xref py py-obj docutils literal"><span class="pre">Panel.reindex</span></code></a>（[items，major_axis，minor_axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2403">使用可选填充逻辑将面板与新索引对齐，将NA / NaN放在前一个索引中没有值的位置。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2404"><a class="reference internal" href="generated/pandas.Panel.reindex_axis.html#pandas.Panel.reindex_axis" title="pandas.Panel.reindex_axis"><code class="xref py py-obj docutils literal"><span class="pre">Panel.reindex_axis</span></code></a>（标签[，axis，method，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2405">使用可选填充逻辑将输入对象与新索引一致，将NA / NaN放在前一个索引中没有值的位置。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2406"><a class="reference internal" href="generated/pandas.Panel.reindex_like.html#pandas.Panel.reindex_like" title="pandas.Panel.reindex_like"><code class="xref py py-obj docutils literal"><span class="pre">Panel.reindex_like</span></code></a>（其他[，方法，副本，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2407">将具有匹配索引的对象返回给我自己。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2408"><a class="reference internal" href="generated/pandas.Panel.rename.html#pandas.Panel.rename" title="pandas.Panel.rename"><code class="xref py py-obj docutils literal"><span class="pre">Panel.rename</span></code></a>（[items，major_axis，minor_axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2409">改变轴输入功能。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2410"><a class="reference internal" href="generated/pandas.Panel.sample.html#pandas.Panel.sample" title="pandas.Panel.sample"><code class="xref py py-obj docutils literal"><span class="pre">Panel.sample</span></code></a>（[n，frac，replace，weights，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2411">从对象的轴返回项目的随机样本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2412"><a class="reference internal" href="generated/pandas.Panel.select.html#pandas.Panel.select" title="pandas.Panel.select"><code class="xref py py-obj docutils literal"><span class="pre">Panel.select</span></code></a>（crit [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2413">返回与轴标签匹配条件相对应的数据</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2414"><a class="reference internal" href="generated/pandas.Panel.take.html#pandas.Panel.take" title="pandas.Panel.take"><code class="xref py py-obj docutils literal"><span class="pre">Panel.take</span></code></a>（索引[，axis，convert，is_copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-2415">类似于ndarray.take</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2416"><a class="reference internal" href="generated/pandas.Panel.truncate.html#pandas.Panel.truncate" title="pandas.Panel.truncate"><code class="xref py py-obj docutils literal"><span class="pre">Panel.truncate</span></code></a>（[before，after，axis，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-2417">在某个特定索引值之前和/或之后截断排序的NDFrame。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id19">
<h3><span class="yiyi-st" id="yiyi-2418">缺少数据处理</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2419"><a class="reference internal" href="generated/pandas.Panel.dropna.html#pandas.Panel.dropna" title="pandas.Panel.dropna"><code class="xref py py-obj docutils literal"><span class="pre">Panel.dropna</span></code></a>（[axis，how，inplace]）</span></td>
<td><span class="yiyi-st" id="yiyi-2420">从面板下降2D，保持通过轴不变</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2421"><a class="reference internal" href="generated/pandas.Panel.fillna.html#pandas.Panel.fillna" title="pandas.Panel.fillna"><code class="xref py py-obj docutils literal"><span class="pre">Panel.fillna</span></code></a>（[value，method，axis，inplace，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2422">使用指定的方法填充NA / NaN值</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id20">
<h3><span class="yiyi-st" id="yiyi-2423">重新整形，排序，转置</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2424"><a class="reference internal" href="generated/pandas.Panel.sort_index.html#pandas.Panel.sort_index" title="pandas.Panel.sort_index"><code class="xref py py-obj docutils literal"><span class="pre">Panel.sort_index</span></code></a>（[axis，level，ascending，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2425">按标签（沿轴）对对象排序</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2426"><a class="reference internal" href="generated/pandas.Panel.swaplevel.html#pandas.Panel.swaplevel" title="pandas.Panel.swaplevel"><code class="xref py py-obj docutils literal"><span class="pre">Panel.swaplevel</span></code></a>（[i，j，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2427">在特定轴上的多索引中交换级别i和j</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2428"><a class="reference internal" href="generated/pandas.Panel.transpose.html#pandas.Panel.transpose" title="pandas.Panel.transpose"><code class="xref py py-obj docutils literal"><span class="pre">Panel.transpose</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2429">请选择面板的尺寸</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2430"><a class="reference internal" href="generated/pandas.Panel.swapaxes.html#pandas.Panel.swapaxes" title="pandas.Panel.swapaxes"><code class="xref py py-obj docutils literal"><span class="pre">Panel.swapaxes</span></code></a>（axis1，axis2 [，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-2431">适当地互换轴和交换值轴</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2432"><a class="reference internal" href="generated/pandas.Panel.conform.html#pandas.Panel.conform" title="pandas.Panel.conform"><code class="xref py py-obj docutils literal"><span class="pre">Panel.conform</span></code></a>（框架[，轴]）</span></td>
<td><span class="yiyi-st" id="yiyi-2433">符合输入DataFrame以与所选轴对对齐。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id21">
<h3><span class="yiyi-st" id="yiyi-2434">组合/加入/合并</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2435"><a class="reference internal" href="generated/pandas.Panel.join.html#pandas.Panel.join" title="pandas.Panel.join"><code class="xref py py-obj docutils literal"><span class="pre">Panel.join</span></code></a>（other [，how，lsuffix，rsuffix]）</span></td>
<td><span class="yiyi-st" id="yiyi-2436">加入项目与其他面板在主轴和次轴列</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2437"><a class="reference internal" href="generated/pandas.Panel.update.html#pandas.Panel.update" title="pandas.Panel.update"><code class="xref py py-obj docutils literal"><span class="pre">Panel.update</span></code></a>（其他[，join，覆盖，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2438">使用来自传递的面板的非NA值或面板强制的对象修改面板。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id22">
<h3><span class="yiyi-st" id="yiyi-2439">时间序列相关的</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2440"><a class="reference internal" href="generated/pandas.Panel.asfreq.html#pandas.Panel.asfreq" title="pandas.Panel.asfreq"><code class="xref py py-obj docutils literal"><span class="pre">Panel.asfreq</span></code></a>（freq [，method，how，normalize]）</span></td>
<td><span class="yiyi-st" id="yiyi-2441">将TimeSeries转换为指定的频率。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2442"><a class="reference internal" href="generated/pandas.Panel.shift.html#pandas.Panel.shift" title="pandas.Panel.shift"><code class="xref py py-obj docutils literal"><span class="pre">Panel.shift</span></code></a>（[periods，freq，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2443">使用可选的时间频率按期望的周期数切换索引。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2444"><a class="reference internal" href="generated/pandas.Panel.resample.html#pandas.Panel.resample" title="pandas.Panel.resample"><code class="xref py py-obj docutils literal"><span class="pre">Panel.resample</span></code></a>（rule [，how，axis，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2445">时间序列的频率转换和重采样的方便方法。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2446"><a class="reference internal" href="generated/pandas.Panel.tz_convert.html#pandas.Panel.tz_convert" title="pandas.Panel.tz_convert"><code class="xref py py-obj docutils literal"><span class="pre">Panel.tz_convert</span></code></a>（tz [，axis，level，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-2447">将tz感知轴转换为目标时区。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2448"><a class="reference internal" href="generated/pandas.Panel.tz_localize.html#pandas.Panel.tz_localize" title="pandas.Panel.tz_localize"><code class="xref py py-obj docutils literal"><span class="pre">Panel.tz_localize</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2449">将tz-naive TimeSeries本地化为目标时区。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id23">
<h3><span class="yiyi-st" id="yiyi-2450">序列化/ IO /转换</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2451"><a class="reference internal" href="generated/pandas.Panel.from_dict.html#pandas.Panel.from_dict" title="pandas.Panel.from_dict"><code class="xref py py-obj docutils literal"><span class="pre">Panel.from_dict</span></code></a>（data [，intersect，orient，dtype]）</span></td>
<td><span class="yiyi-st" id="yiyi-2452">根据DataFrame对象的dict构造面板</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2453"><a class="reference internal" href="generated/pandas.Panel.to_pickle.html#pandas.Panel.to_pickle" title="pandas.Panel.to_pickle"><code class="xref py py-obj docutils literal"><span class="pre">Panel.to_pickle</span></code></a>（路径）</span></td>
<td><span class="yiyi-st" id="yiyi-2454">Pickle（序列化）对象到输入文件路径。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2455"><a class="reference internal" href="generated/pandas.Panel.to_excel.html#pandas.Panel.to_excel" title="pandas.Panel.to_excel"><code class="xref py py-obj docutils literal"><span class="pre">Panel.to_excel</span></code></a>（path [，na_rep，engine]）</span></td>
<td><span class="yiyi-st" id="yiyi-2456">将Panel中的每个DataFrame写入单独的Excel表单</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2457"><a class="reference internal" href="generated/pandas.Panel.to_hdf.html#pandas.Panel.to_hdf" title="pandas.Panel.to_hdf"><code class="xref py py-obj docutils literal"><span class="pre">Panel.to_hdf</span></code></a>（path_or_buf，key，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2458">使用HDFStore将包含的数据写入HDF5文件。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2459"><a class="reference internal" href="generated/pandas.Panel.to_sparse.html#pandas.Panel.to_sparse" title="pandas.Panel.to_sparse"><code class="xref py py-obj docutils literal"><span class="pre">Panel.to_sparse</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2460">NOT IMPLEMENTED：不调用此方法，因为面板对象不支持稀疏化，并且会引发错误。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2461"><a class="reference internal" href="generated/pandas.Panel.to_frame.html#pandas.Panel.to_frame" title="pandas.Panel.to_frame"><code class="xref py py-obj docutils literal"><span class="pre">Panel.to_frame</span></code></a>（[filter_observations]）</span></td>
<td><span class="yiyi-st" id="yiyi-2462">将宽格式转换为长（堆叠）格式为DataFrame，其列是Panel的项目，其索引是由Panel的长轴和短轴组成的MultiIndex。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2463"><a class="reference internal" href="generated/pandas.Panel.to_xarray.html#pandas.Panel.to_xarray" title="pandas.Panel.to_xarray"><code class="xref py py-obj docutils literal"><span class="pre">Panel.to_xarray</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2464">从pandas对象返回一个xarray对象。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2465"><a class="reference internal" href="generated/pandas.Panel.to_clipboard.html#pandas.Panel.to_clipboard" title="pandas.Panel.to_clipboard"><code class="xref py py-obj docutils literal"><span class="pre">Panel.to_clipboard</span></code></a>（[excel，sep]）</span></td>
<td><span class="yiyi-st" id="yiyi-2466">尝试将对象的文本表示写入系统剪贴板例如，可以将其粘贴到Excel中。</span></td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section" id="panel4d">
<span id="api-panel4d"></span><h2><span class="yiyi-st" id="yiyi-2467">Panel4D</span></h2>
<div class="section" id="id24">
<h3><span class="yiyi-st" id="yiyi-2468">构造</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2469"><a class="reference internal" href="generated/pandas.Panel4D.html#pandas.Panel4D" title="pandas.Panel4D"><code class="xref py py-obj docutils literal"><span class="pre">Panel4D</span></code></a>（[data，labels，items，major_axis，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2470">Panel4D是一个4维命名容器，非常像一个Panel，但有4个命名维度。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id25">
<h3><span class="yiyi-st" id="yiyi-2471">序列化/ IO /转换</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2472"><a class="reference internal" href="generated/pandas.Panel4D.to_xarray.html#pandas.Panel4D.to_xarray" title="pandas.Panel4D.to_xarray"><code class="xref py py-obj docutils literal"><span class="pre">Panel4D.to_xarray</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2473">从pandas对象返回一个xarray对象。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id26">
<h3><span class="yiyi-st" id="yiyi-2474">属性和底层数据</span></h3>
<p><span class="yiyi-st" id="yiyi-2475"><strong>轴</strong></span></p>
<blockquote>
<div><ul class="simple">
<li><span class="yiyi-st" id="yiyi-2476"><strong>标签</strong>：轴1；每个标签对应一个包含在里面的Panel</span></li>
<li><span class="yiyi-st" id="yiyi-2477"><strong>项</strong>：轴2；每个项目对应于其中包含的DataFrame</span></li>
<li><span class="yiyi-st" id="yiyi-2478"><strong>major_axis</strong>：轴3；每个DataFrames的索引（行）</span></li>
<li><span class="yiyi-st" id="yiyi-2479"><strong>minor_axis</strong>：轴4；每个DataFrames的列</span></li>
</ul>
</div></blockquote>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2480"><a class="reference internal" href="generated/pandas.Panel4D.values.html#pandas.Panel4D.values" title="pandas.Panel4D.values"><code class="xref py py-obj docutils literal"><span class="pre">Panel4D.values</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2481">NDFrame的块状表示</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2482"><a class="reference internal" href="generated/pandas.Panel4D.axes.html#pandas.Panel4D.axes" title="pandas.Panel4D.axes"><code class="xref py py-obj docutils literal"><span class="pre">Panel4D.axes</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2483">返回内部NDFrame的索引标签</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2484"><a class="reference internal" href="generated/pandas.Panel4D.ndim.html#pandas.Panel4D.ndim" title="pandas.Panel4D.ndim"><code class="xref py py-obj docutils literal"><span class="pre">Panel4D.ndim</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2485">轴数/阵列尺寸</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2486"><a class="reference internal" href="generated/pandas.Panel4D.size.html#pandas.Panel4D.size" title="pandas.Panel4D.size"><code class="xref py py-obj docutils literal"><span class="pre">Panel4D.size</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2487">NDFrame中的元素数</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2488"><a class="reference internal" href="generated/pandas.Panel4D.shape.html#pandas.Panel4D.shape" title="pandas.Panel4D.shape"><code class="xref py py-obj docutils literal"><span class="pre">Panel4D.shape</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2489">返回轴维度的元组</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2490"><a class="reference internal" href="generated/pandas.Panel4D.dtypes.html#pandas.Panel4D.dtypes" title="pandas.Panel4D.dtypes"><code class="xref py py-obj docutils literal"><span class="pre">Panel4D.dtypes</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2491">返回此对象中的dtype。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2492"><a class="reference internal" href="generated/pandas.Panel4D.ftypes.html#pandas.Panel4D.ftypes" title="pandas.Panel4D.ftypes"><code class="xref py py-obj docutils literal"><span class="pre">Panel4D.ftypes</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2493">返回此对象中的ftypes（稀疏/密集和dtype的指示）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2494"><a class="reference internal" href="generated/pandas.Panel4D.get_dtype_counts.html#pandas.Panel4D.get_dtype_counts" title="pandas.Panel4D.get_dtype_counts"><code class="xref py py-obj docutils literal"><span class="pre">Panel4D.get_dtype_counts</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2495">返回此对象中的dtypes的计数。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2496"><a class="reference internal" href="generated/pandas.Panel4D.get_ftype_counts.html#pandas.Panel4D.get_ftype_counts" title="pandas.Panel4D.get_ftype_counts"><code class="xref py py-obj docutils literal"><span class="pre">Panel4D.get_ftype_counts</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2497">返回此对象中的ftypes的计数。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id27">
<h3><span class="yiyi-st" id="yiyi-2498">转换</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2499"><a class="reference internal" href="generated/pandas.Panel4D.astype.html#pandas.Panel4D.astype" title="pandas.Panel4D.astype"><code class="xref py py-obj docutils literal"><span class="pre">Panel4D.astype</span></code></a>（dtype [，copy，raise_on_error]）</span></td>
<td><span class="yiyi-st" id="yiyi-2500">投射对象以输入numpy.dtype</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2501"><a class="reference internal" href="generated/pandas.Panel4D.copy.html#pandas.Panel4D.copy" title="pandas.Panel4D.copy"><code class="xref py py-obj docutils literal"><span class="pre">Panel4D.copy</span></code></a>（[deep]）</span></td>
<td><span class="yiyi-st" id="yiyi-2502">复制此对象数据。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2503"><a class="reference internal" href="generated/pandas.Panel4D.isnull.html#pandas.Panel4D.isnull" title="pandas.Panel4D.isnull"><code class="xref py py-obj docutils literal"><span class="pre">Panel4D.isnull</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2504">返回一个布尔大小相同的对象，指示值是否为null。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2505"><a class="reference internal" href="generated/pandas.Panel4D.notnull.html#pandas.Panel4D.notnull" title="pandas.Panel4D.notnull"><code class="xref py py-obj docutils literal"><span class="pre">Panel4D.notnull</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2506">返回一个布尔大小相同的对象，指示这些值是否为空。</span></td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section" id="index">
<span id="api-index"></span><h2><span class="yiyi-st" id="yiyi-2507">指数</span></h2>
<p><span class="yiyi-st" id="yiyi-2508"><strong>这些方法或其变体中的许多可用于包含索引（Series / Dataframe）的对象，并且在直接调用这些方法之前应该最有可能使用这些方法或变体。</strong></span></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2509"><a class="reference internal" href="generated/pandas.Index.html#pandas.Index" title="pandas.Index"><code class="xref py py-obj docutils literal"><span class="pre">Index</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2510">不可变的ndarray实现有序的，可分割的集合。</span></td>
</tr>
</tbody>
</table>
<div class="section" id="id28">
<h3><span class="yiyi-st" id="yiyi-2511">属性</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2512"><a class="reference internal" href="generated/pandas.Index.values.html#pandas.Index.values" title="pandas.Index.values"><code class="xref py py-obj docutils literal"><span class="pre">Index.values</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2513">将底层数据作为ndarray返回</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2514"><a class="reference internal" href="generated/pandas.Index.is_monotonic.html#pandas.Index.is_monotonic" title="pandas.Index.is_monotonic"><code class="xref py py-obj docutils literal"><span class="pre">Index.is_monotonic</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2515">is_monotonic_increasing的别名（已弃用）</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2516"><a class="reference internal" href="generated/pandas.Index.is_monotonic_increasing.html#pandas.Index.is_monotonic_increasing" title="pandas.Index.is_monotonic_increasing"><code class="xref py py-obj docutils literal"><span class="pre">Index.is_monotonic_increasing</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2517">返回如果索引是单调递增（只等于或</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2518"><a class="reference internal" href="generated/pandas.Index.is_monotonic_decreasing.html#pandas.Index.is_monotonic_decreasing" title="pandas.Index.is_monotonic_decreasing"><code class="xref py py-obj docutils literal"><span class="pre">Index.is_monotonic_decreasing</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2519">返回如果索引是单调递减（只等于或</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2520"><a class="reference internal" href="generated/pandas.Index.is_unique.html#pandas.Index.is_unique" title="pandas.Index.is_unique"><code class="xref py py-obj docutils literal"><span class="pre">Index.is_unique</span></code></a></span></td>
<td></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2521"><a class="reference internal" href="generated/pandas.Index.has_duplicates.html#pandas.Index.has_duplicates" title="pandas.Index.has_duplicates"><code class="xref py py-obj docutils literal"><span class="pre">Index.has_duplicates</span></code></a></span></td>
<td></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2522"><a class="reference internal" href="generated/pandas.Index.dtype.html#pandas.Index.dtype" title="pandas.Index.dtype"><code class="xref py py-obj docutils literal"><span class="pre">Index.dtype</span></code></a></span></td>
<td></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2523"><a class="reference internal" href="generated/pandas.Index.inferred_type.html#pandas.Index.inferred_type" title="pandas.Index.inferred_type"><code class="xref py py-obj docutils literal"><span class="pre">Index.inferred_type</span></code></a></span></td>
<td></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2524"><a class="reference internal" href="generated/pandas.Index.is_all_dates.html#pandas.Index.is_all_dates" title="pandas.Index.is_all_dates"><code class="xref py py-obj docutils literal"><span class="pre">Index.is_all_dates</span></code></a></span></td>
<td></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2525"><a class="reference internal" href="generated/pandas.Index.shape.html#pandas.Index.shape" title="pandas.Index.shape"><code class="xref py py-obj docutils literal"><span class="pre">Index.shape</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2526">返回基础数据的形状的元组</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2527"><a class="reference internal" href="generated/pandas.Index.nbytes.html#pandas.Index.nbytes" title="pandas.Index.nbytes"><code class="xref py py-obj docutils literal"><span class="pre">Index.nbytes</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2528">返回底层数据中的字节数</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2529"><a class="reference internal" href="generated/pandas.Index.ndim.html#pandas.Index.ndim" title="pandas.Index.ndim"><code class="xref py py-obj docutils literal"><span class="pre">Index.ndim</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2530">返回底层数据的维数，</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2531"><a class="reference internal" href="generated/pandas.Index.size.html#pandas.Index.size" title="pandas.Index.size"><code class="xref py py-obj docutils literal"><span class="pre">Index.size</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2532">返回底层数据中的元素数量</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2533"><a class="reference internal" href="generated/pandas.Index.strides.html#pandas.Index.strides" title="pandas.Index.strides"><code class="xref py py-obj docutils literal"><span class="pre">Index.strides</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2534">返回基础数据的步幅</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2535"><a class="reference internal" href="generated/pandas.Index.itemsize.html#pandas.Index.itemsize" title="pandas.Index.itemsize"><code class="xref py py-obj docutils literal"><span class="pre">Index.itemsize</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2536">返回底层数据项的dtype的大小</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2537"><a class="reference internal" href="generated/pandas.Index.base.html#pandas.Index.base" title="pandas.Index.base"><code class="xref py py-obj docutils literal"><span class="pre">Index.base</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2538">如果基础数据的内存是，则返回基础对象</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2539"><a class="reference internal" href="generated/pandas.Index.T.html#pandas.Index.T" title="pandas.Index.T"><code class="xref py py-obj docutils literal"><span class="pre">Index.T</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2540">返回转置，这是通过定义self</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2541"><a class="reference internal" href="generated/pandas.Index.memory_usage.html#pandas.Index.memory_usage" title="pandas.Index.memory_usage"><code class="xref py py-obj docutils literal"><span class="pre">Index.memory_usage</span></code></a>（[deep]）</span></td>
<td><span class="yiyi-st" id="yiyi-2542">我的值的内存使用</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="modifying-and-computations">
<h3><span class="yiyi-st" id="yiyi-2543">修改和计算</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2544"><a class="reference internal" href="generated/pandas.Index.all.html#pandas.Index.all" title="pandas.Index.all"><code class="xref py py-obj docutils literal"><span class="pre">Index.all</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2545">返回所有元素是否为True</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2546"><a class="reference internal" href="generated/pandas.Index.any.html#pandas.Index.any" title="pandas.Index.any"><code class="xref py py-obj docutils literal"><span class="pre">Index.any</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2547">返回任何元素是否为True</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2548"><a class="reference internal" href="generated/pandas.Index.argmin.html#pandas.Index.argmin" title="pandas.Index.argmin"><code class="xref py py-obj docutils literal"><span class="pre">Index.argmin</span></code></a>（[axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2549">返回最小参数索引器的数组</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2550"><a class="reference internal" href="generated/pandas.Index.argmax.html#pandas.Index.argmax" title="pandas.Index.argmax"><code class="xref py py-obj docutils literal"><span class="pre">Index.argmax</span></code></a>（[axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2551">返回最大参数索引器的一个ndarray</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2552"><a class="reference internal" href="generated/pandas.Index.copy.html#pandas.Index.copy" title="pandas.Index.copy"><code class="xref py py-obj docutils literal"><span class="pre">Index.copy</span></code></a>（[name，deep，dtype]）</span></td>
<td><span class="yiyi-st" id="yiyi-2553">制作此对象的副本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2554"><a class="reference internal" href="generated/pandas.Index.delete.html#pandas.Index.delete" title="pandas.Index.delete"><code class="xref py py-obj docutils literal"><span class="pre">Index.delete</span></code></a>（loc）</span></td>
<td><span class="yiyi-st" id="yiyi-2555">删除已传递位置（-s）的新建索引</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2556"><a class="reference internal" href="generated/pandas.Index.drop.html#pandas.Index.drop" title="pandas.Index.drop"><code class="xref py py-obj docutils literal"><span class="pre">Index.drop</span></code></a>（labels [，errors]）</span></td>
<td><span class="yiyi-st" id="yiyi-2557">创建新索引，并删除已通过的标签列表</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2558"><a class="reference internal" href="generated/pandas.Index.drop_duplicates.html#pandas.Index.drop_duplicates" title="pandas.Index.drop_duplicates"><code class="xref py py-obj docutils literal"><span class="pre">Index.drop_duplicates</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2559">返回索引，重复值已删除</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2560"><a class="reference internal" href="generated/pandas.Index.duplicated.html#pandas.Index.duplicated" title="pandas.Index.duplicated"><code class="xref py py-obj docutils literal"><span class="pre">Index.duplicated</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2561">返回boolean np.ndarray表示重复值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2562"><a class="reference internal" href="generated/pandas.Index.equals.html#pandas.Index.equals" title="pandas.Index.equals"><code class="xref py py-obj docutils literal"><span class="pre">Index.equals</span></code></a>（other）</span></td>
<td><span class="yiyi-st" id="yiyi-2563">确定两个Index对象是否包含相同的元素。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2564"><a class="reference internal" href="generated/pandas.Index.factorize.html#pandas.Index.factorize" title="pandas.Index.factorize"><code class="xref py py-obj docutils literal"><span class="pre">Index.factorize</span></code></a>（[sort，na_sentinel]）</span></td>
<td><span class="yiyi-st" id="yiyi-2565">将对象编码为枚举类型或类别变量</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2566"><a class="reference internal" href="generated/pandas.Index.identical.html#pandas.Index.identical" title="pandas.Index.identical"><code class="xref py py-obj docutils literal"><span class="pre">Index.identical</span></code></a>（other）</span></td>
<td><span class="yiyi-st" id="yiyi-2567">类似于equals，但检查其他类似的属性</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2568"><a class="reference internal" href="generated/pandas.Index.insert.html#pandas.Index.insert" title="pandas.Index.insert"><code class="xref py py-obj docutils literal"><span class="pre">Index.insert</span></code></a>（loc，item）</span></td>
<td><span class="yiyi-st" id="yiyi-2569">使新索引在位置插入新项目。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2570"><a class="reference internal" href="generated/pandas.Index.min.html#pandas.Index.min" title="pandas.Index.min"><code class="xref py py-obj docutils literal"><span class="pre">Index.min</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2571">对象的最小值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2572"><a class="reference internal" href="generated/pandas.Index.max.html#pandas.Index.max" title="pandas.Index.max"><code class="xref py py-obj docutils literal"><span class="pre">Index.max</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2573">对象的最大值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2574"><a class="reference internal" href="generated/pandas.Index.reindex.html#pandas.Index.reindex" title="pandas.Index.reindex"><code class="xref py py-obj docutils literal"><span class="pre">Index.reindex</span></code></a>（target [，method，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2575">使用目标值创建索引（根据需要移动/添加/删除值）</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2576"><a class="reference internal" href="generated/pandas.Index.repeat.html#pandas.Index.repeat" title="pandas.Index.repeat"><code class="xref py py-obj docutils literal"><span class="pre">Index.repeat</span></code></a>（n，\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2577">重复索引的元素。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2578"><a class="reference internal" href="generated/pandas.Index.where.html#pandas.Index.where" title="pandas.Index.where"><code class="xref py py-obj docutils literal"><span class="pre">Index.where</span></code></a>（cond [，other]）</span></td>
<td><div class="versionadded">
<p><span class="yiyi-st" id="yiyi-2579"><span class="versionmodified">版本0.19.0中的新功能。</span></span></p>
</div>
</td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2580"><a class="reference internal" href="generated/pandas.Index.take.html#pandas.Index.take" title="pandas.Index.take"><code class="xref py py-obj docutils literal"><span class="pre">Index.take</span></code></a>（indices [，axis，allow_fill，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2581">返回由索引选择的值的新的％（klass）</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2582"><a class="reference internal" href="generated/pandas.Index.putmask.html#pandas.Index.putmask" title="pandas.Index.putmask"><code class="xref py py-obj docutils literal"><span class="pre">Index.putmask</span></code></a>（mask，value）</span></td>
<td><span class="yiyi-st" id="yiyi-2583">返回使用掩码设置的值的新索引</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2584"><a class="reference internal" href="generated/pandas.Index.set_names.html#pandas.Index.set_names" title="pandas.Index.set_names"><code class="xref py py-obj docutils literal"><span class="pre">Index.set_names</span></code></a>（names [，level，inplace]）</span></td>
<td><span class="yiyi-st" id="yiyi-2585">在索引上设置新名称。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2586"><a class="reference internal" href="generated/pandas.Index.unique.html#pandas.Index.unique" title="pandas.Index.unique"><code class="xref py py-obj docutils literal"><span class="pre">Index.unique</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2587">返回对象中唯一值的索引。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2588"><a class="reference internal" href="generated/pandas.Index.nunique.html#pandas.Index.nunique" title="pandas.Index.nunique"><code class="xref py py-obj docutils literal"><span class="pre">Index.nunique</span></code></a>（[dropna]）</span></td>
<td><span class="yiyi-st" id="yiyi-2589">返回对象中唯一元素的数量。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2590"><a class="reference internal" href="generated/pandas.Index.value_counts.html#pandas.Index.value_counts" title="pandas.Index.value_counts"><code class="xref py py-obj docutils literal"><span class="pre">Index.value_counts</span></code></a>（[normalize，sort，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2591">返回包含唯一值计数的对象。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2592"><a class="reference internal" href="generated/pandas.Index.fillna.html#pandas.Index.fillna" title="pandas.Index.fillna"><code class="xref py py-obj docutils literal"><span class="pre">Index.fillna</span></code></a>（[value，downcast]）</span></td>
<td><span class="yiyi-st" id="yiyi-2593">用指定值填充NA / NaN值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2594"><a class="reference internal" href="generated/pandas.Index.dropna.html#pandas.Index.dropna" title="pandas.Index.dropna"><code class="xref py py-obj docutils literal"><span class="pre">Index.dropna</span></code></a>（[how]）</span></td>
<td><span class="yiyi-st" id="yiyi-2595">无NA / NaN值的返回索引</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id29">
<h3><span class="yiyi-st" id="yiyi-2596">转换</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2597"><a class="reference internal" href="generated/pandas.Index.astype.html#pandas.Index.astype" title="pandas.Index.astype"><code class="xref py py-obj docutils literal"><span class="pre">Index.astype</span></code></a>（dtype [，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-2598">创建一个值转换为dtypes的索引。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2599"><a class="reference internal" href="generated/pandas.Index.tolist.html#pandas.Index.tolist" title="pandas.Index.tolist"><code class="xref py py-obj docutils literal"><span class="pre">Index.tolist</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2600">返回索引值的列表</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2601"><a class="reference internal" href="generated/pandas.Index.to_datetime.html#pandas.Index.to_datetime" title="pandas.Index.to_datetime"><code class="xref py py-obj docutils literal"><span class="pre">Index.to_datetime</span></code></a>（[dayfirst]）</span></td>
<td><span class="yiyi-st" id="yiyi-2602">DEPRECATED：改用<a class="reference internal" href="generated/pandas.to_datetime.html#pandas.to_datetime" title="pandas.to_datetime"><code class="xref py py-meth docutils literal"><span class="pre">pandas.to_datetime()</span></code></a>。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2603"><a class="reference internal" href="generated/pandas.Index.to_series.html#pandas.Index.to_series" title="pandas.Index.to_series"><code class="xref py py-obj docutils literal"><span class="pre">Index.to_series</span></code></a>（\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2604">创建索引和值都等于索引键的系列</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="sorting">
<h3><span class="yiyi-st" id="yiyi-2605">排序</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2606"><a class="reference internal" href="generated/pandas.Index.argsort.html#pandas.Index.argsort" title="pandas.Index.argsort"><code class="xref py py-obj docutils literal"><span class="pre">Index.argsort</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2607">返回将索引及其基础数据排序的索引。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2608"><a class="reference internal" href="generated/pandas.Index.sort_values.html#pandas.Index.sort_values" title="pandas.Index.sort_values"><code class="xref py py-obj docutils literal"><span class="pre">Index.sort_values</span></code></a>（[return_indexer，ascending]）</span></td>
<td><span class="yiyi-st" id="yiyi-2609">返回Index的排序副本</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="time-specific-operations">
<h3><span class="yiyi-st" id="yiyi-2610">时间特定的操作</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2611"><a class="reference internal" href="generated/pandas.Index.shift.html#pandas.Index.shift" title="pandas.Index.shift"><code class="xref py py-obj docutils literal"><span class="pre">Index.shift</span></code></a>（[periods，freq]）</span></td>
<td><span class="yiyi-st" id="yiyi-2612">Shift包含datetime对象的索引按输入的句点数和</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="combining-joining-set-operations">
<h3><span class="yiyi-st" id="yiyi-2613">组合/加入/集合操作</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2614"><a class="reference internal" href="generated/pandas.Index.append.html#pandas.Index.append" title="pandas.Index.append"><code class="xref py py-obj docutils literal"><span class="pre">Index.append</span></code></a>（other）</span></td>
<td><span class="yiyi-st" id="yiyi-2615">将索引选项集合附加在一起</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2616"><a class="reference internal" href="generated/pandas.Index.join.html#pandas.Index.join" title="pandas.Index.join"><code class="xref py py-obj docutils literal"><span class="pre">Index.join</span></code></a>（other [，how，level，return_indexers]）</span></td>
<td><span class="yiyi-st" id="yiyi-2617"><em>这是一个内部非公开方法</em></span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2618"><a class="reference internal" href="generated/pandas.Index.intersection.html#pandas.Index.intersection" title="pandas.Index.intersection"><code class="xref py py-obj docutils literal"><span class="pre">Index.intersection</span></code></a>（other）</span></td>
<td><span class="yiyi-st" id="yiyi-2619">形成两个Index对象。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2620"><a class="reference internal" href="generated/pandas.Index.union.html#pandas.Index.union" title="pandas.Index.union"><code class="xref py py-obj docutils literal"><span class="pre">Index.union</span></code></a>（其他）</span></td>
<td><span class="yiyi-st" id="yiyi-2621">如果可能，形成两个Index对象的并集，并排序。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2622"><a class="reference internal" href="generated/pandas.Index.difference.html#pandas.Index.difference" title="pandas.Index.difference"><code class="xref py py-obj docutils literal"><span class="pre">Index.difference</span></code></a>（other）</span></td>
<td><span class="yiyi-st" id="yiyi-2623">返回索引中不在<cite>其他</cite>中的元素的新索引。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2624"><a class="reference internal" href="generated/pandas.Index.symmetric_difference.html#pandas.Index.symmetric_difference" title="pandas.Index.symmetric_difference"><code class="xref py py-obj docutils literal"><span class="pre">Index.symmetric_difference</span></code></a>（other [，result_name]）</span></td>
<td><span class="yiyi-st" id="yiyi-2625">计算两个Index对象的对称差异。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="selecting">
<h3><span class="yiyi-st" id="yiyi-2626">选择</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2627"><a class="reference internal" href="generated/pandas.Index.get_indexer.html#pandas.Index.get_indexer" title="pandas.Index.get_indexer"><code class="xref py py-obj docutils literal"><span class="pre">Index.get_indexer</span></code></a>（target [，method，limit，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2628">给定当前索引的新索引的计算索引器和掩码。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2629"><a class="reference internal" href="generated/pandas.Index.get_indexer_non_unique.html#pandas.Index.get_indexer_non_unique" title="pandas.Index.get_indexer_non_unique"><code class="xref py py-obj docutils literal"><span class="pre">Index.get_indexer_non_unique</span></code></a>（target）</span></td>
<td><span class="yiyi-st" id="yiyi-2630">返回适合从非唯一索引获取的索引器</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2631"><a class="reference internal" href="generated/pandas.Index.get_level_values.html#pandas.Index.get_level_values" title="pandas.Index.get_level_values"><code class="xref py py-obj docutils literal"><span class="pre">Index.get_level_values</span></code></a>（level）</span></td>
<td><span class="yiyi-st" id="yiyi-2632">所请求级别的标签值的返回向量，等于长度</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2633"><a class="reference internal" href="generated/pandas.Index.get_loc.html#pandas.Index.get_loc" title="pandas.Index.get_loc"><code class="xref py py-obj docutils literal"><span class="pre">Index.get_loc</span></code></a>（key [，method，tolerance]）</span></td>
<td><span class="yiyi-st" id="yiyi-2634">获取所请求标签的整数位置</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2635"><a class="reference internal" href="generated/pandas.Index.get_value.html#pandas.Index.get_value" title="pandas.Index.get_value"><code class="xref py py-obj docutils literal"><span class="pre">Index.get_value</span></code></a>（series，key）</span></td>
<td><span class="yiyi-st" id="yiyi-2636">从1维数组中快速查找值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2637"><a class="reference internal" href="generated/pandas.Index.isin.html#pandas.Index.isin" title="pandas.Index.isin"><code class="xref py py-obj docutils literal"><span class="pre">Index.isin</span></code></a>（values [，level]）</span></td>
<td><span class="yiyi-st" id="yiyi-2638">计算每个索引值是否在传递的值集中找到的布尔数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2639"><a class="reference internal" href="generated/pandas.Index.slice_indexer.html#pandas.Index.slice_indexer" title="pandas.Index.slice_indexer"><code class="xref py py-obj docutils literal"><span class="pre">Index.slice_indexer</span></code></a>（[start，end，step，kind]）</span></td>
<td><span class="yiyi-st" id="yiyi-2640">对于有序索引，计算输入标签和的切片索引器</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2641"><a class="reference internal" href="generated/pandas.Index.slice_locs.html#pandas.Index.slice_locs" title="pandas.Index.slice_locs"><code class="xref py py-obj docutils literal"><span class="pre">Index.slice_locs</span></code></a>（[start，end，step，kind]）</span></td>
<td><span class="yiyi-st" id="yiyi-2642">计算输入标签的切片位置。</span></td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section" id="categoricalindex">
<span id="api-categoricalindex"></span><h2><span class="yiyi-st" id="yiyi-2643">CategoricalIndex</span></h2>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2644"><a class="reference internal" href="generated/pandas.CategoricalIndex.html#pandas.CategoricalIndex" title="pandas.CategoricalIndex"><code class="xref py py-obj docutils literal"><span class="pre">CategoricalIndex</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2645">不可变索引实现有序，可分割集。</span></td>
</tr>
</tbody>
</table>
<div class="section" id="categorical-components">
<h3><span class="yiyi-st" id="yiyi-2646">分类组件</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2647"><a class="reference internal" href="generated/pandas.CategoricalIndex.codes.html#pandas.CategoricalIndex.codes" title="pandas.CategoricalIndex.codes"><code class="xref py py-obj docutils literal"><span class="pre">CategoricalIndex.codes</span></code></a></span></td>
<td></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2648"><a class="reference internal" href="generated/pandas.CategoricalIndex.categories.html#pandas.CategoricalIndex.categories" title="pandas.CategoricalIndex.categories"><code class="xref py py-obj docutils literal"><span class="pre">CategoricalIndex.categories</span></code></a></span></td>
<td></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2649"><a class="reference internal" href="generated/pandas.CategoricalIndex.ordered.html#pandas.CategoricalIndex.ordered" title="pandas.CategoricalIndex.ordered"><code class="xref py py-obj docutils literal"><span class="pre">CategoricalIndex.ordered</span></code></a></span></td>
<td></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2650"><a class="reference internal" href="generated/pandas.CategoricalIndex.rename_categories.html#pandas.CategoricalIndex.rename_categories" title="pandas.CategoricalIndex.rename_categories"><code class="xref py py-obj docutils literal"><span class="pre">CategoricalIndex.rename_categories</span></code></a>（\ * args，...）</span></td>
<td><span class="yiyi-st" id="yiyi-2651">重命名类别。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2652"><a class="reference internal" href="generated/pandas.CategoricalIndex.reorder_categories.html#pandas.CategoricalIndex.reorder_categories" title="pandas.CategoricalIndex.reorder_categories"><code class="xref py py-obj docutils literal"><span class="pre">CategoricalIndex.reorder_categories</span></code></a>（\ * args，...）</span></td>
<td><span class="yiyi-st" id="yiyi-2653">重新排序在new_categories中指定的类别。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2654"><a class="reference internal" href="generated/pandas.CategoricalIndex.add_categories.html#pandas.CategoricalIndex.add_categories" title="pandas.CategoricalIndex.add_categories"><code class="xref py py-obj docutils literal"><span class="pre">CategoricalIndex.add_categories</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2655">添加新类别。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2656"><a class="reference internal" href="generated/pandas.CategoricalIndex.remove_categories.html#pandas.CategoricalIndex.remove_categories" title="pandas.CategoricalIndex.remove_categories"><code class="xref py py-obj docutils literal"><span class="pre">CategoricalIndex.remove_categories</span></code></a>（\ * args，...）</span></td>
<td><span class="yiyi-st" id="yiyi-2657">删除指定的类别。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2658"><a class="reference internal" href="generated/pandas.CategoricalIndex.remove_unused_categories.html#pandas.CategoricalIndex.remove_unused_categories" title="pandas.CategoricalIndex.remove_unused_categories"><code class="xref py py-obj docutils literal"><span class="pre">CategoricalIndex.remove_unused_categories</span></code></a>（...）</span></td>
<td><span class="yiyi-st" id="yiyi-2659">删除未使用的类别。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2660"><a class="reference internal" href="generated/pandas.CategoricalIndex.set_categories.html#pandas.CategoricalIndex.set_categories" title="pandas.CategoricalIndex.set_categories"><code class="xref py py-obj docutils literal"><span class="pre">CategoricalIndex.set_categories</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2661">将类别设置为指定的new_categories。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2662"><a class="reference internal" href="generated/pandas.CategoricalIndex.as_ordered.html#pandas.CategoricalIndex.as_ordered" title="pandas.CategoricalIndex.as_ordered"><code class="xref py py-obj docutils literal"><span class="pre">CategoricalIndex.as_ordered</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2663">设置要排序的分类</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2664"><a class="reference internal" href="generated/pandas.CategoricalIndex.as_unordered.html#pandas.CategoricalIndex.as_unordered" title="pandas.CategoricalIndex.as_unordered"><code class="xref py py-obj docutils literal"><span class="pre">CategoricalIndex.as_unordered</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2665">将分类设置为无序</span></td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section" id="multiindex">
<span id="api-multiindex"></span><h2><span class="yiyi-st" id="yiyi-2666">多指标</span></h2>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2667"><a class="reference internal" href="generated/pandas.MultiIndex.html#pandas.MultiIndex" title="pandas.MultiIndex"><code class="xref py py-obj docutils literal"><span class="pre">MultiIndex</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2668">用于大熊猫对象的多级或分层索引对象</span></td>
</tr>
</tbody>
</table>
<div class="section" id="multiindex-components">
<h3><span class="yiyi-st" id="yiyi-2669">MultiIndex组件</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2670"><a class="reference internal" href="generated/pandas.MultiIndex.from_arrays.html#pandas.MultiIndex.from_arrays" title="pandas.MultiIndex.from_arrays"><code class="xref py py-obj docutils literal"><span class="pre">MultiIndex.from_arrays</span></code></a>（arrays [，sortorder，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2671">将数组转换为MultiIndex</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2672"><a class="reference internal" href="generated/pandas.MultiIndex.from_tuples.html#pandas.MultiIndex.from_tuples" title="pandas.MultiIndex.from_tuples"><code class="xref py py-obj docutils literal"><span class="pre">MultiIndex.from_tuples</span></code></a>（tuples [，sortorder，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2673">将元组列表转换为MultiIndex</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2674"><a class="reference internal" href="generated/pandas.MultiIndex.from_product.html#pandas.MultiIndex.from_product" title="pandas.MultiIndex.from_product"><code class="xref py py-obj docutils literal"><span class="pre">MultiIndex.from_product</span></code></a>（iterables [，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2675">从多个迭代的笛卡尔乘积生成多索引</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2676"><a class="reference internal" href="generated/pandas.MultiIndex.set_levels.html#pandas.MultiIndex.set_levels" title="pandas.MultiIndex.set_levels"><code class="xref py py-obj docutils literal"><span class="pre">MultiIndex.set_levels</span></code></a>（levels [，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2677">在MultiIndex上设置新级别。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2678"><a class="reference internal" href="generated/pandas.MultiIndex.set_labels.html#pandas.MultiIndex.set_labels" title="pandas.MultiIndex.set_labels"><code class="xref py py-obj docutils literal"><span class="pre">MultiIndex.set_labels</span></code></a>（labels [，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2679">在MultiIndex上设置新标签。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2680"><a class="reference internal" href="generated/pandas.MultiIndex.to_hierarchical.html#pandas.MultiIndex.to_hierarchical" title="pandas.MultiIndex.to_hierarchical"><code class="xref py py-obj docutils literal"><span class="pre">MultiIndex.to_hierarchical</span></code></a>（n_repeat [，n_shuffle]）</span></td>
<td><span class="yiyi-st" id="yiyi-2681">返回一个重定形的MultiIndex，以符合n_repeat和n_shuffle给出的形状。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2682"><a class="reference internal" href="generated/pandas.MultiIndex.is_lexsorted.html#pandas.MultiIndex.is_lexsorted" title="pandas.MultiIndex.is_lexsorted"><code class="xref py py-obj docutils literal"><span class="pre">MultiIndex.is_lexsorted</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2683">如果标签按字典顺序排序，则返回True</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2684"><a class="reference internal" href="generated/pandas.MultiIndex.droplevel.html#pandas.MultiIndex.droplevel" title="pandas.MultiIndex.droplevel"><code class="xref py py-obj docutils literal"><span class="pre">MultiIndex.droplevel</span></code></a>（[level]）</span></td>
<td><span class="yiyi-st" id="yiyi-2685">返回已删除请求级别的索引。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2686"><a class="reference internal" href="generated/pandas.MultiIndex.swaplevel.html#pandas.MultiIndex.swaplevel" title="pandas.MultiIndex.swaplevel"><code class="xref py py-obj docutils literal"><span class="pre">MultiIndex.swaplevel</span></code></a>（[i，j]）</span></td>
<td><span class="yiyi-st" id="yiyi-2687">将级别i与级别j交换。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2688"><a class="reference internal" href="generated/pandas.MultiIndex.reorder_levels.html#pandas.MultiIndex.reorder_levels" title="pandas.MultiIndex.reorder_levels"><code class="xref py py-obj docutils literal"><span class="pre">MultiIndex.reorder_levels</span></code></a>（order）</span></td>
<td><span class="yiyi-st" id="yiyi-2689">使用输入顺序重新排列级别。</span></td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section" id="datetimeindex">
<span id="api-datetimeindex"></span><h2><span class="yiyi-st" id="yiyi-2690">DatetimeIndex</span></h2>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2691"><a class="reference internal" href="generated/pandas.DatetimeIndex.html#pandas.DatetimeIndex" title="pandas.DatetimeIndex"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2692">datetime64数据的不可变的ndarray，在内部表示为int64，并且可以装箱到作为datetime的子类的Timestamp对象并携带诸如频率信息的元数据。</span></td>
</tr>
</tbody>
</table>
<div class="section" id="time-date-components">
<h3><span class="yiyi-st" id="yiyi-2693">时间/日期组件</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2694"><a class="reference internal" href="generated/pandas.DatetimeIndex.year.html#pandas.DatetimeIndex.year" title="pandas.DatetimeIndex.year"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.year</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2695">datetime的年份</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2696"><a class="reference internal" href="generated/pandas.DatetimeIndex.month.html#pandas.DatetimeIndex.month" title="pandas.DatetimeIndex.month"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.month</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2697">月份为1月= 1月，12月= 12月</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2698"><a class="reference internal" href="generated/pandas.DatetimeIndex.day.html#pandas.DatetimeIndex.day" title="pandas.DatetimeIndex.day"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.day</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2699">datetime的日期</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2700"><a class="reference internal" href="generated/pandas.DatetimeIndex.hour.html#pandas.DatetimeIndex.hour" title="pandas.DatetimeIndex.hour"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.hour</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2701">datetime的小时数</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2702"><a class="reference internal" href="generated/pandas.DatetimeIndex.minute.html#pandas.DatetimeIndex.minute" title="pandas.DatetimeIndex.minute"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.minute</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2703">datetime的分钟</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2704"><a class="reference internal" href="generated/pandas.DatetimeIndex.second.html#pandas.DatetimeIndex.second" title="pandas.DatetimeIndex.second"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.second</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2705">datetime的秒数</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2706"><a class="reference internal" href="generated/pandas.DatetimeIndex.microsecond.html#pandas.DatetimeIndex.microsecond" title="pandas.DatetimeIndex.microsecond"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.microsecond</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2707">datetime的微秒</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2708"><a class="reference internal" href="generated/pandas.DatetimeIndex.nanosecond.html#pandas.DatetimeIndex.nanosecond" title="pandas.DatetimeIndex.nanosecond"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.nanosecond</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2709">datetime的纳秒</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2710"><a class="reference internal" href="generated/pandas.DatetimeIndex.date.html#pandas.DatetimeIndex.date" title="pandas.DatetimeIndex.date"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.date</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2711">返回numpy数组的python datetime.date对象（即，没有时区信息的时间戳的日期部分）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2712"><a class="reference internal" href="generated/pandas.DatetimeIndex.time.html#pandas.DatetimeIndex.time" title="pandas.DatetimeIndex.time"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.time</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2713">返回datetime.time的numpy数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2714"><a class="reference internal" href="generated/pandas.DatetimeIndex.dayofyear.html#pandas.DatetimeIndex.dayofyear" title="pandas.DatetimeIndex.dayofyear"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.dayofyear</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2715">一年的序数日</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2716"><a class="reference internal" href="generated/pandas.DatetimeIndex.weekofyear.html#pandas.DatetimeIndex.weekofyear" title="pandas.DatetimeIndex.weekofyear"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.weekofyear</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2717">一年的周数</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2718"><a class="reference internal" href="generated/pandas.DatetimeIndex.week.html#pandas.DatetimeIndex.week" title="pandas.DatetimeIndex.week"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.week</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2719">一年的周数</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2720"><a class="reference internal" href="generated/pandas.DatetimeIndex.dayofweek.html#pandas.DatetimeIndex.dayofweek" title="pandas.DatetimeIndex.dayofweek"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.dayofweek</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2721">一周中的星期几，星期一= 0，星期六= 6</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2722"><a class="reference internal" href="generated/pandas.DatetimeIndex.weekday.html#pandas.DatetimeIndex.weekday" title="pandas.DatetimeIndex.weekday"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.weekday</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2723">一周中的星期几，星期一= 0，星期六= 6</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2724"><a class="reference internal" href="generated/pandas.DatetimeIndex.weekday_name.html#pandas.DatetimeIndex.weekday_name" title="pandas.DatetimeIndex.weekday_name"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.weekday_name</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2725">一周中的日期名称（例如：星期五）</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2726"><a class="reference internal" href="generated/pandas.DatetimeIndex.quarter.html#pandas.DatetimeIndex.quarter" title="pandas.DatetimeIndex.quarter"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.quarter</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2727">日期的四分之一</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2728"><a class="reference internal" href="generated/pandas.DatetimeIndex.tz.html#pandas.DatetimeIndex.tz" title="pandas.DatetimeIndex.tz"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.tz</span></code></a></span></td>
<td></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2729"><a class="reference internal" href="generated/pandas.DatetimeIndex.freq.html#pandas.DatetimeIndex.freq" title="pandas.DatetimeIndex.freq"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.freq</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2730">获取/设置索引的频率</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2731"><a class="reference internal" href="generated/pandas.DatetimeIndex.freqstr.html#pandas.DatetimeIndex.freqstr" title="pandas.DatetimeIndex.freqstr"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.freqstr</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2732">如果它的设置返回频率对象作为字符串，否则返回None</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2733"><a class="reference internal" href="generated/pandas.DatetimeIndex.is_month_start.html#pandas.DatetimeIndex.is_month_start" title="pandas.DatetimeIndex.is_month_start"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.is_month_start</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2734">逻辑指示是否每月的第一天（由频率定义）</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2735"><a class="reference internal" href="generated/pandas.DatetimeIndex.is_month_end.html#pandas.DatetimeIndex.is_month_end" title="pandas.DatetimeIndex.is_month_end"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.is_month_end</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2736">逻辑指示是否每月的最后一天（由频率定义）</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2737"><a class="reference internal" href="generated/pandas.DatetimeIndex.is_quarter_start.html#pandas.DatetimeIndex.is_quarter_start" title="pandas.DatetimeIndex.is_quarter_start"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.is_quarter_start</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2738">逻辑指示季度的第一天（由频率定义）</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2739"><a class="reference internal" href="generated/pandas.DatetimeIndex.is_quarter_end.html#pandas.DatetimeIndex.is_quarter_end" title="pandas.DatetimeIndex.is_quarter_end"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.is_quarter_end</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2740">逻辑指示季度的最后一天（由频率定义）</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2741"><a class="reference internal" href="generated/pandas.DatetimeIndex.is_year_start.html#pandas.DatetimeIndex.is_year_start" title="pandas.DatetimeIndex.is_year_start"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.is_year_start</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2742">逻辑指示一年中的第一天（由频率定义）</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2743"><a class="reference internal" href="generated/pandas.DatetimeIndex.is_year_end.html#pandas.DatetimeIndex.is_year_end" title="pandas.DatetimeIndex.is_year_end"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.is_year_end</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2744">逻辑指示一年中的最后一天（由频率定义）</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2745"><a class="reference internal" href="generated/pandas.DatetimeIndex.is_leap_year.html#pandas.DatetimeIndex.is_leap_year" title="pandas.DatetimeIndex.is_leap_year"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.is_leap_year</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2746">逻辑指示日期是否属于闰年</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2747"><a class="reference internal" href="generated/pandas.DatetimeIndex.inferred_freq.html#pandas.DatetimeIndex.inferred_freq" title="pandas.DatetimeIndex.inferred_freq"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.inferred_freq</span></code></a></span></td>
<td></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id30">
<h3><span class="yiyi-st" id="yiyi-2748">选择</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2749"><a class="reference internal" href="generated/pandas.DatetimeIndex.indexer_at_time.html#pandas.DatetimeIndex.indexer_at_time" title="pandas.DatetimeIndex.indexer_at_time"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.indexer_at_time</span></code></a>（time [，asof]）</span></td>
<td><span class="yiyi-st" id="yiyi-2750">在特定时段选择值（例如</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2751"><a class="reference internal" href="generated/pandas.DatetimeIndex.indexer_between_time.html#pandas.DatetimeIndex.indexer_between_time" title="pandas.DatetimeIndex.indexer_between_time"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.indexer_between_time</span></code></a>（... [，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2752">在一天中的特定时间之间选择值（例如，9：00-9：30AM）。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id31">
<h3><span class="yiyi-st" id="yiyi-2753">时间特定的操作</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2754"><a class="reference internal" href="generated/pandas.DatetimeIndex.normalize.html#pandas.DatetimeIndex.normalize" title="pandas.DatetimeIndex.normalize"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.normalize</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2755">将DatetimeIndex与时间返回到午夜。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2756"><a class="reference internal" href="generated/pandas.DatetimeIndex.strftime.html#pandas.DatetimeIndex.strftime" title="pandas.DatetimeIndex.strftime"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.strftime</span></code></a>（date_format）</span></td>
<td><span class="yiyi-st" id="yiyi-2757">返回由date_format指定的格式化字符串数组，该数组支持与python标准库相同的字符串格式。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2758"><a class="reference internal" href="generated/pandas.DatetimeIndex.snap.html#pandas.DatetimeIndex.snap" title="pandas.DatetimeIndex.snap"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.snap</span></code></a>（[freq]）</span></td>
<td><span class="yiyi-st" id="yiyi-2759">捕捉时间戳到最近发生的频率</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2760"><a class="reference internal" href="generated/pandas.DatetimeIndex.tz_convert.html#pandas.DatetimeIndex.tz_convert" title="pandas.DatetimeIndex.tz_convert"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.tz_convert</span></code></a>（tz）</span></td>
<td><span class="yiyi-st" id="yiyi-2761">将tz感知DatetimeIndex从一个时区转换到另一个（使用</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2762"><a class="reference internal" href="generated/pandas.DatetimeIndex.tz_localize.html#pandas.DatetimeIndex.tz_localize" title="pandas.DatetimeIndex.tz_localize"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.tz_localize</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2763">将tz-naive DatetimeIndex本地化到给定时区（使用</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2764"><a class="reference internal" href="generated/pandas.DatetimeIndex.round.html#pandas.DatetimeIndex.round" title="pandas.DatetimeIndex.round"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.round</span></code></a>（freq，\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2765">将索引循环到指定的频率</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2766"><a class="reference internal" href="generated/pandas.DatetimeIndex.floor.html#pandas.DatetimeIndex.floor" title="pandas.DatetimeIndex.floor"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.floor</span></code></a>（freq）</span></td>
<td><span class="yiyi-st" id="yiyi-2767">将索引落到指定的频率</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2768"><a class="reference internal" href="generated/pandas.DatetimeIndex.ceil.html#pandas.DatetimeIndex.ceil" title="pandas.DatetimeIndex.ceil"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.ceil</span></code></a>（freq）</span></td>
<td><span class="yiyi-st" id="yiyi-2769">ceil索引到指定的频率</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id32">
<h3><span class="yiyi-st" id="yiyi-2770">转换</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2771"><a class="reference internal" href="generated/pandas.DatetimeIndex.to_datetime.html#pandas.DatetimeIndex.to_datetime" title="pandas.DatetimeIndex.to_datetime"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.to_datetime</span></code></a>（[dayfirst]）</span></td>
<td></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2772"><a class="reference internal" href="generated/pandas.DatetimeIndex.to_period.html#pandas.DatetimeIndex.to_period" title="pandas.DatetimeIndex.to_period"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.to_period</span></code></a>（[freq]）</span></td>
<td><span class="yiyi-st" id="yiyi-2773">以特定频率投射到PeriodIndex</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2774"><a class="reference internal" href="generated/pandas.DatetimeIndex.to_perioddelta.html#pandas.DatetimeIndex.to_perioddelta" title="pandas.DatetimeIndex.to_perioddelta"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.to_perioddelta</span></code></a>（freq）</span></td>
<td><span class="yiyi-st" id="yiyi-2775">计算指数值与在指定频率下转换为PeriodIndex的指数之间的差的TimedeltaIndex。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2776"><a class="reference internal" href="generated/pandas.DatetimeIndex.to_pydatetime.html#pandas.DatetimeIndex.to_pydatetime" title="pandas.DatetimeIndex.to_pydatetime"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.to_pydatetime</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2777">返回DatetimeIndex作为datetime.datetime对象的对象ndarray</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2778"><a class="reference internal" href="generated/pandas.DatetimeIndex.to_series.html#pandas.DatetimeIndex.to_series" title="pandas.DatetimeIndex.to_series"><code class="xref py py-obj docutils literal"><span class="pre">DatetimeIndex.to_series</span></code></a>（[keep_tz]）</span></td>
<td><span class="yiyi-st" id="yiyi-2779">创建索引和值都等于索引键的系列</span></td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section" id="timedeltaindex">
<h2><span class="yiyi-st" id="yiyi-2780">TimedeltaIndex</span></h2>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2781"><a class="reference internal" href="generated/pandas.TimedeltaIndex.html#pandas.TimedeltaIndex" title="pandas.TimedeltaIndex"><code class="xref py py-obj docutils literal"><span class="pre">TimedeltaIndex</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2782">timedelta64数据的不可变的ndarray，在内部表示为int64，和</span></td>
</tr>
</tbody>
</table>
<div class="section" id="components">
<h3><span class="yiyi-st" id="yiyi-2783">部件</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2784"><a class="reference internal" href="generated/pandas.TimedeltaIndex.days.html#pandas.TimedeltaIndex.days" title="pandas.TimedeltaIndex.days"><code class="xref py py-obj docutils literal"><span class="pre">TimedeltaIndex.days</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2785">每个元素的天数。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2786"><a class="reference internal" href="generated/pandas.TimedeltaIndex.seconds.html#pandas.TimedeltaIndex.seconds" title="pandas.TimedeltaIndex.seconds"><code class="xref py py-obj docutils literal"><span class="pre">TimedeltaIndex.seconds</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2787">每个元素的秒数（&gt; = 0和小于1天）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2788"><a class="reference internal" href="generated/pandas.TimedeltaIndex.microseconds.html#pandas.TimedeltaIndex.microseconds" title="pandas.TimedeltaIndex.microseconds"><code class="xref py py-obj docutils literal"><span class="pre">TimedeltaIndex.microseconds</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2789">每个元素的微秒数（&gt; = 0和小于1秒）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2790"><a class="reference internal" href="generated/pandas.TimedeltaIndex.nanoseconds.html#pandas.TimedeltaIndex.nanoseconds" title="pandas.TimedeltaIndex.nanoseconds"><code class="xref py py-obj docutils literal"><span class="pre">TimedeltaIndex.nanoseconds</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2791">每个元素的纳秒数（&gt; = 0和小于1微秒）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2792"><a class="reference internal" href="generated/pandas.TimedeltaIndex.components.html#pandas.TimedeltaIndex.components" title="pandas.TimedeltaIndex.components"><code class="xref py py-obj docutils literal"><span class="pre">TimedeltaIndex.components</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2793">返回Timedeltas的组件（天，小时，分钟，秒，毫秒，微秒，纳秒）的数据帧。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2794"><a class="reference internal" href="generated/pandas.TimedeltaIndex.inferred_freq.html#pandas.TimedeltaIndex.inferred_freq" title="pandas.TimedeltaIndex.inferred_freq"><code class="xref py py-obj docutils literal"><span class="pre">TimedeltaIndex.inferred_freq</span></code></a></span></td>
<td></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id33">
<h3><span class="yiyi-st" id="yiyi-2795">转换</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2796"><a class="reference internal" href="generated/pandas.TimedeltaIndex.to_pytimedelta.html#pandas.TimedeltaIndex.to_pytimedelta" title="pandas.TimedeltaIndex.to_pytimedelta"><code class="xref py py-obj docutils literal"><span class="pre">TimedeltaIndex.to_pytimedelta</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2797">返回TimedeltaIndex作为datetime.timedelta对象的对象ndarray</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2798"><a class="reference internal" href="generated/pandas.TimedeltaIndex.to_series.html#pandas.TimedeltaIndex.to_series" title="pandas.TimedeltaIndex.to_series"><code class="xref py py-obj docutils literal"><span class="pre">TimedeltaIndex.to_series</span></code></a>（\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2799">创建索引和值都等于索引键的系列</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2800"><a class="reference internal" href="generated/pandas.TimedeltaIndex.round.html#pandas.TimedeltaIndex.round" title="pandas.TimedeltaIndex.round"><code class="xref py py-obj docutils literal"><span class="pre">TimedeltaIndex.round</span></code></a>（freq，\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2801">将索引循环到指定的频率</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2802"><a class="reference internal" href="generated/pandas.TimedeltaIndex.floor.html#pandas.TimedeltaIndex.floor" title="pandas.TimedeltaIndex.floor"><code class="xref py py-obj docutils literal"><span class="pre">TimedeltaIndex.floor</span></code></a>（freq）</span></td>
<td><span class="yiyi-st" id="yiyi-2803">将索引落到指定的频率</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2804"><a class="reference internal" href="generated/pandas.TimedeltaIndex.ceil.html#pandas.TimedeltaIndex.ceil" title="pandas.TimedeltaIndex.ceil"><code class="xref py py-obj docutils literal"><span class="pre">TimedeltaIndex.ceil</span></code></a>（freq）</span></td>
<td><span class="yiyi-st" id="yiyi-2805">ceil索引到指定的频率</span></td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section" id="window">
<h2><span class="yiyi-st" id="yiyi-2806">窗口</span></h2>
<p><span class="yiyi-st" id="yiyi-2807">滚动对象由<code class="docutils literal"><span class="pre">.rolling</span></code>调用：<a class="reference internal" href="generated/pandas.DataFrame.rolling.html#pandas.DataFrame.rolling" title="pandas.DataFrame.rolling"><code class="xref py py-func docutils literal"><span class="pre">pandas.DataFrame.rolling()</span></code></a>，<a class="reference internal" href="generated/pandas.Series.rolling.html#pandas.Series.rolling" title="pandas.Series.rolling"><code class="xref py py-func docutils literal"><span class="pre">pandas.Series.rolling()</span></code></a>等返回。</span><span class="yiyi-st" id="yiyi-2808">展开对象通过<code class="docutils literal"><span class="pre">.expanding</span></code>调用：<a class="reference internal" href="generated/pandas.DataFrame.expanding.html#pandas.DataFrame.expanding" title="pandas.DataFrame.expanding"><code class="xref py py-func docutils literal"><span class="pre">pandas.DataFrame.expanding()</span></code></a>，<a class="reference internal" href="generated/pandas.Series.expanding.html#pandas.Series.expanding" title="pandas.Series.expanding"><code class="xref py py-func docutils literal"><span class="pre">pandas.Series.expanding()</span></code></a>等返回。</span><span class="yiyi-st" id="yiyi-2809">EWM对象由<code class="docutils literal"><span class="pre">.ewm</span></code>调用：<a class="reference internal" href="generated/pandas.DataFrame.ewm.html#pandas.DataFrame.ewm" title="pandas.DataFrame.ewm"><code class="xref py py-func docutils literal"><span class="pre">pandas.DataFrame.ewm()</span></code></a>，<a class="reference internal" href="generated/pandas.Series.ewm.html#pandas.Series.ewm" title="pandas.Series.ewm"><code class="xref py py-func docutils literal"><span class="pre">pandas.Series.ewm()</span></code></a>等返回。</span></p>
<div class="section" id="standard-moving-window-functions">
<h3><span class="yiyi-st" id="yiyi-2810">标准移动窗口功能</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2811"><a class="reference internal" href="generated/pandas.core.window.Rolling.count.html#pandas.core.window.Rolling.count" title="pandas.core.window.Rolling.count"><code class="xref py py-obj docutils literal"><span class="pre">Rolling.count</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2812">轧制数非NaN数</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2813"><a class="reference internal" href="generated/pandas.core.window.Rolling.sum.html#pandas.core.window.Rolling.sum" title="pandas.core.window.Rolling.sum"><code class="xref py py-obj docutils literal"><span class="pre">Rolling.sum</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2814">滚动总和</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2815"><a class="reference internal" href="generated/pandas.core.window.Rolling.mean.html#pandas.core.window.Rolling.mean" title="pandas.core.window.Rolling.mean"><code class="xref py py-obj docutils literal"><span class="pre">Rolling.mean</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2816">滚动平均值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2817"><a class="reference internal" href="generated/pandas.core.window.Rolling.median.html#pandas.core.window.Rolling.median" title="pandas.core.window.Rolling.median"><code class="xref py py-obj docutils literal"><span class="pre">Rolling.median</span></code></a>（\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2818">滚动中值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2819"><a class="reference internal" href="generated/pandas.core.window.Rolling.var.html#pandas.core.window.Rolling.var" title="pandas.core.window.Rolling.var"><code class="xref py py-obj docutils literal"><span class="pre">Rolling.var</span></code></a>（[ddof]）</span></td>
<td><span class="yiyi-st" id="yiyi-2820">滚动方差</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2821"><a class="reference internal" href="generated/pandas.core.window.Rolling.std.html#pandas.core.window.Rolling.std" title="pandas.core.window.Rolling.std"><code class="xref py py-obj docutils literal"><span class="pre">Rolling.std</span></code></a>（[ddof]）</span></td>
<td><span class="yiyi-st" id="yiyi-2822">轧制标准偏差</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2823"><a class="reference internal" href="generated/pandas.core.window.Rolling.min.html#pandas.core.window.Rolling.min" title="pandas.core.window.Rolling.min"><code class="xref py py-obj docutils literal"><span class="pre">Rolling.min</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2824">滚动最小</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2825"><a class="reference internal" href="generated/pandas.core.window.Rolling.max.html#pandas.core.window.Rolling.max" title="pandas.core.window.Rolling.max"><code class="xref py py-obj docutils literal"><span class="pre">Rolling.max</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2826">轧制最大</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2827"><a class="reference internal" href="generated/pandas.core.window.Rolling.corr.html#pandas.core.window.Rolling.corr" title="pandas.core.window.Rolling.corr"><code class="xref py py-obj docutils literal"><span class="pre">Rolling.corr</span></code></a>（[other，pairwise]）</span></td>
<td><span class="yiyi-st" id="yiyi-2828">滚动采样相关</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2829"><a class="reference internal" href="generated/pandas.core.window.Rolling.cov.html#pandas.core.window.Rolling.cov" title="pandas.core.window.Rolling.cov"><code class="xref py py-obj docutils literal"><span class="pre">Rolling.cov</span></code></a>（[other，pairwise，ddof]）</span></td>
<td><span class="yiyi-st" id="yiyi-2830">滚动样本协方差</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2831"><a class="reference internal" href="generated/pandas.core.window.Rolling.skew.html#pandas.core.window.Rolling.skew" title="pandas.core.window.Rolling.skew"><code class="xref py py-obj docutils literal"><span class="pre">Rolling.skew</span></code></a>（\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2832">无偏斜歪斜</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2833"><a class="reference internal" href="generated/pandas.core.window.Rolling.kurt.html#pandas.core.window.Rolling.kurt" title="pandas.core.window.Rolling.kurt"><code class="xref py py-obj docutils literal"><span class="pre">Rolling.kurt</span></code></a>（\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2834">无偏的滚动峭度</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2835"><a class="reference internal" href="generated/pandas.core.window.Rolling.apply.html#pandas.core.window.Rolling.apply" title="pandas.core.window.Rolling.apply"><code class="xref py py-obj docutils literal"><span class="pre">Rolling.apply</span></code></a>（func [，args，kwargs]）</span></td>
<td><span class="yiyi-st" id="yiyi-2836">滚动功能适用</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2837"><a class="reference internal" href="generated/pandas.core.window.Rolling.quantile.html#pandas.core.window.Rolling.quantile" title="pandas.core.window.Rolling.quantile"><code class="xref py py-obj docutils literal"><span class="pre">Rolling.quantile</span></code></a>（quantile，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2838">滚动分位数</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2839"><a class="reference internal" href="generated/pandas.core.window.Window.mean.html#pandas.core.window.Window.mean" title="pandas.core.window.Window.mean"><code class="xref py py-obj docutils literal"><span class="pre">Window.mean</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2840">窗口平均值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2841"><a class="reference internal" href="generated/pandas.core.window.Window.sum.html#pandas.core.window.Window.sum" title="pandas.core.window.Window.sum"><code class="xref py py-obj docutils literal"><span class="pre">Window.sum</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2842">窗口总和</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="standard-expanding-window-functions">
<span id="api-functions-expanding"></span><h3><span class="yiyi-st" id="yiyi-2843">标准扩展窗口函数</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2844"><a class="reference internal" href="generated/pandas.core.window.Expanding.count.html#pandas.core.window.Expanding.count" title="pandas.core.window.Expanding.count"><code class="xref py py-obj docutils literal"><span class="pre">Expanding.count</span></code></a>（\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2845">扩展非NaN的数量</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2846"><a class="reference internal" href="generated/pandas.core.window.Expanding.sum.html#pandas.core.window.Expanding.sum" title="pandas.core.window.Expanding.sum"><code class="xref py py-obj docutils literal"><span class="pre">Expanding.sum</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2847">扩大和</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2848"><a class="reference internal" href="generated/pandas.core.window.Expanding.mean.html#pandas.core.window.Expanding.mean" title="pandas.core.window.Expanding.mean"><code class="xref py py-obj docutils literal"><span class="pre">Expanding.mean</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2849">扩展均值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2850"><a class="reference internal" href="generated/pandas.core.window.Expanding.median.html#pandas.core.window.Expanding.median" title="pandas.core.window.Expanding.median"><code class="xref py py-obj docutils literal"><span class="pre">Expanding.median</span></code></a>（\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2851">扩张中值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2852"><a class="reference internal" href="generated/pandas.core.window.Expanding.var.html#pandas.core.window.Expanding.var" title="pandas.core.window.Expanding.var"><code class="xref py py-obj docutils literal"><span class="pre">Expanding.var</span></code></a>（[ddof]）</span></td>
<td><span class="yiyi-st" id="yiyi-2853">扩展方差</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2854"><a class="reference internal" href="generated/pandas.core.window.Expanding.std.html#pandas.core.window.Expanding.std" title="pandas.core.window.Expanding.std"><code class="xref py py-obj docutils literal"><span class="pre">Expanding.std</span></code></a>（[ddof]）</span></td>
<td><span class="yiyi-st" id="yiyi-2855">扩大标准差</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2856"><a class="reference internal" href="generated/pandas.core.window.Expanding.min.html#pandas.core.window.Expanding.min" title="pandas.core.window.Expanding.min"><code class="xref py py-obj docutils literal"><span class="pre">Expanding.min</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2857">扩大最小</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2858"><a class="reference internal" href="generated/pandas.core.window.Expanding.max.html#pandas.core.window.Expanding.max" title="pandas.core.window.Expanding.max"><code class="xref py py-obj docutils literal"><span class="pre">Expanding.max</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2859">膨胀最大</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2860"><a class="reference internal" href="generated/pandas.core.window.Expanding.corr.html#pandas.core.window.Expanding.corr" title="pandas.core.window.Expanding.corr"><code class="xref py py-obj docutils literal"><span class="pre">Expanding.corr</span></code></a>（[other，pairwise]）</span></td>
<td><span class="yiyi-st" id="yiyi-2861">扩大样本相关性</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2862"><a class="reference internal" href="generated/pandas.core.window.Expanding.cov.html#pandas.core.window.Expanding.cov" title="pandas.core.window.Expanding.cov"><code class="xref py py-obj docutils literal"><span class="pre">Expanding.cov</span></code></a>（[other，pairwise，ddof]）</span></td>
<td><span class="yiyi-st" id="yiyi-2863">扩大样本协方差</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2864"><a class="reference internal" href="generated/pandas.core.window.Expanding.skew.html#pandas.core.window.Expanding.skew" title="pandas.core.window.Expanding.skew"><code class="xref py py-obj docutils literal"><span class="pre">Expanding.skew</span></code></a>（\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2865">无偏的扩展偏度</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2866"><a class="reference internal" href="generated/pandas.core.window.Expanding.kurt.html#pandas.core.window.Expanding.kurt" title="pandas.core.window.Expanding.kurt"><code class="xref py py-obj docutils literal"><span class="pre">Expanding.kurt</span></code></a>（\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2867">无偏膨胀峭度</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2868"><a class="reference internal" href="generated/pandas.core.window.Expanding.apply.html#pandas.core.window.Expanding.apply" title="pandas.core.window.Expanding.apply"><code class="xref py py-obj docutils literal"><span class="pre">Expanding.apply</span></code></a>（func [，args，kwargs]）</span></td>
<td><span class="yiyi-st" id="yiyi-2869">扩展功能</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2870"><a class="reference internal" href="generated/pandas.core.window.Expanding.quantile.html#pandas.core.window.Expanding.quantile" title="pandas.core.window.Expanding.quantile"><code class="xref py py-obj docutils literal"><span class="pre">Expanding.quantile</span></code></a>（quantile，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2871">扩展分位数</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="exponentially-weighted-moving-window-functions">
<h3><span class="yiyi-st" id="yiyi-2872">指数加权移动窗口函数</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2873"><a class="reference internal" href="generated/pandas.core.window.EWM.mean.html#pandas.core.window.EWM.mean" title="pandas.core.window.EWM.mean"><code class="xref py py-obj docutils literal"><span class="pre">EWM.mean</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2874">指数加权移动平均</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2875"><a class="reference internal" href="generated/pandas.core.window.EWM.std.html#pandas.core.window.EWM.std" title="pandas.core.window.EWM.std"><code class="xref py py-obj docutils literal"><span class="pre">EWM.std</span></code></a>（[bias]）</span></td>
<td><span class="yiyi-st" id="yiyi-2876">指数加权移动stddev</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2877"><a class="reference internal" href="generated/pandas.core.window.EWM.var.html#pandas.core.window.EWM.var" title="pandas.core.window.EWM.var"><code class="xref py py-obj docutils literal"><span class="pre">EWM.var</span></code></a>（[bias]）</span></td>
<td><span class="yiyi-st" id="yiyi-2878">指数加权移动方差</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2879"><a class="reference internal" href="generated/pandas.core.window.EWM.corr.html#pandas.core.window.EWM.corr" title="pandas.core.window.EWM.corr"><code class="xref py py-obj docutils literal"><span class="pre">EWM.corr</span></code></a>（[other，pairwise]）</span></td>
<td><span class="yiyi-st" id="yiyi-2880">指数加权样本相关</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2881"><a class="reference internal" href="generated/pandas.core.window.EWM.cov.html#pandas.core.window.EWM.cov" title="pandas.core.window.EWM.cov"><code class="xref py py-obj docutils literal"><span class="pre">EWM.cov</span></code></a>（[other，pairwise，bias]）</span></td>
<td><span class="yiyi-st" id="yiyi-2882">指数加权样本协方差</span></td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section" id="groupby">
<h2><span class="yiyi-st" id="yiyi-2883">GroupBy</span></h2>
<p><span class="yiyi-st" id="yiyi-2884">GroupBy对象由groupby调用返回：<a class="reference internal" href="generated/pandas.DataFrame.groupby.html#pandas.DataFrame.groupby" title="pandas.DataFrame.groupby"><code class="xref py py-func docutils literal"><span class="pre">pandas.DataFrame.groupby()</span></code></a>，<a class="reference internal" href="generated/pandas.Series.groupby.html#pandas.Series.groupby" title="pandas.Series.groupby"><code class="xref py py-func docutils literal"><span class="pre">pandas.Series.groupby()</span></code></a>等。</span></p>
<div class="section" id="id34">
<h3><span class="yiyi-st" id="yiyi-2885">索引，迭代</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2886"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.__iter__.html#pandas.core.groupby.GroupBy.__iter__" title="pandas.core.groupby.GroupBy.__iter__"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.__iter__</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2887">Groupby迭代器</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2888"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.groups.html#pandas.core.groupby.GroupBy.groups" title="pandas.core.groupby.GroupBy.groups"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.groups</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2889">dict {group name  - &gt; group labels}</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2890"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.indices.html#pandas.core.groupby.GroupBy.indices" title="pandas.core.groupby.GroupBy.indices"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.indices</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2891">dict {group name  - &gt; group indices}</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2892"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.get_group.html#pandas.core.groupby.GroupBy.get_group" title="pandas.core.groupby.GroupBy.get_group"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.get_group</span></code></a>（name [，obj]）</span></td>
<td><span class="yiyi-st" id="yiyi-2893">从提供的名称的组构造NDFrame</span></td>
</tr>
</tbody>
</table>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2894"><a class="reference internal" href="generated/pandas.Grouper.html#pandas.Grouper" title="pandas.Grouper"><code class="xref py py-obj docutils literal"><span class="pre">Grouper</span></code></a>（[key，level，freq，axis，sort]）</span></td>
<td><span class="yiyi-st" id="yiyi-2895">Grouper允许用户为目标指定groupby指令</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="function-application">
<h3><span class="yiyi-st" id="yiyi-2896">功能应用</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2897"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.apply.html#pandas.core.groupby.GroupBy.apply" title="pandas.core.groupby.GroupBy.apply"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.apply</span></code></a>（func，\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2898">应用功能并以智能方式将结果组合在一起。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2899"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.aggregate.html#pandas.core.groupby.GroupBy.aggregate" title="pandas.core.groupby.GroupBy.aggregate"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.aggregate</span></code></a>（func，\ * args，\ * \ * kwargs）</span></td>
<td></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2900"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.transform.html#pandas.core.groupby.GroupBy.transform" title="pandas.core.groupby.GroupBy.transform"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.transform</span></code></a>（func，\ * args，\ * \ * kwargs）</span></td>
<td></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id35">
<h3><span class="yiyi-st" id="yiyi-2901">计算/描述性统计</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2902"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.count.html#pandas.core.groupby.GroupBy.count" title="pandas.core.groupby.GroupBy.count"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.count</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2903">计算组的计数，不包括缺少的值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2904"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.cumcount.html#pandas.core.groupby.GroupBy.cumcount" title="pandas.core.groupby.GroupBy.cumcount"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.cumcount</span></code></a>（[ascending]）</span></td>
<td><span class="yiyi-st" id="yiyi-2905">将每个组中的每个项从0到该组的长度编号 -  1。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2906"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.first.html#pandas.core.groupby.GroupBy.first" title="pandas.core.groupby.GroupBy.first"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.first</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2907">计算组值的第一个值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2908"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.head.html#pandas.core.groupby.GroupBy.head" title="pandas.core.groupby.GroupBy.head"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.head</span></code></a>（[n]）</span></td>
<td><span class="yiyi-st" id="yiyi-2909">返回每个组的前n行。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2910"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.last.html#pandas.core.groupby.GroupBy.last" title="pandas.core.groupby.GroupBy.last"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.last</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2911">计算组值的最后一个</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2912"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.max.html#pandas.core.groupby.GroupBy.max" title="pandas.core.groupby.GroupBy.max"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.max</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2913">计算组值的最大值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2914"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.mean.html#pandas.core.groupby.GroupBy.mean" title="pandas.core.groupby.GroupBy.mean"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.mean</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2915">计算组的平均值，不包括缺少的值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2916"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.median.html#pandas.core.groupby.GroupBy.median" title="pandas.core.groupby.GroupBy.median"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.median</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2917">计算组的中间值，不包括缺失值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2918"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.min.html#pandas.core.groupby.GroupBy.min" title="pandas.core.groupby.GroupBy.min"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.min</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2919">计算组值的最小值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2920"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.nth.html#pandas.core.groupby.GroupBy.nth" title="pandas.core.groupby.GroupBy.nth"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.nth</span></code></a>（n [，dropna]）</span></td>
<td><span class="yiyi-st" id="yiyi-2921">如果n是一个int，从每个组的第n行，或如果n是一个int列表的行的子集。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2922"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.ohlc.html#pandas.core.groupby.GroupBy.ohlc" title="pandas.core.groupby.GroupBy.ohlc"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.ohlc</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2923">计算值的总和，不包括缺少的值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2924"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.prod.html#pandas.core.groupby.GroupBy.prod" title="pandas.core.groupby.GroupBy.prod"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.prod</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2925">计算组值的prod</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2926"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.size.html#pandas.core.groupby.GroupBy.size" title="pandas.core.groupby.GroupBy.size"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.size</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2927">计算组大小</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2928"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.sem.html#pandas.core.groupby.GroupBy.sem" title="pandas.core.groupby.GroupBy.sem"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.sem</span></code></a>（[ddof]）</span></td>
<td><span class="yiyi-st" id="yiyi-2929">计算组平均值的标准误差，不包括缺失值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2930"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.std.html#pandas.core.groupby.GroupBy.std" title="pandas.core.groupby.GroupBy.std"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.std</span></code></a>（[ddof]）</span></td>
<td><span class="yiyi-st" id="yiyi-2931">计算组的标准偏差，不包括缺失值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2932"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.sum.html#pandas.core.groupby.GroupBy.sum" title="pandas.core.groupby.GroupBy.sum"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.sum</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2933">计算组值的总和</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2934"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.var.html#pandas.core.groupby.GroupBy.var" title="pandas.core.groupby.GroupBy.var"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.var</span></code></a>（[ddof]）</span></td>
<td><span class="yiyi-st" id="yiyi-2935">计算组的方差，不包括缺少的值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2936"><a class="reference internal" href="generated/pandas.core.groupby.GroupBy.tail.html#pandas.core.groupby.GroupBy.tail" title="pandas.core.groupby.GroupBy.tail"><code class="xref py py-obj docutils literal"><span class="pre">GroupBy.tail</span></code></a>（[n]）</span></td>
<td><span class="yiyi-st" id="yiyi-2937">返回每组的后n行</span></td>
</tr>
</tbody>
</table>
<p><span class="yiyi-st" id="yiyi-2938">以下方法在<code class="docutils literal"><span class="pre">SeriesGroupBy</span></code>和<code class="docutils literal"><span class="pre">DataFrameGroupBy</span></code>对象中都可用，但可能稍有不同，通常是因为<code class="docutils literal"><span class="pre">DataFrameGroupBy</span></code>版本通常允许指定轴参数，并且通常指示是否将应用程序限制为特定数据类型的列的参数。</span></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2939"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.agg.html#pandas.core.groupby.DataFrameGroupBy.agg" title="pandas.core.groupby.DataFrameGroupBy.agg"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.agg</span></code></a>（arg，\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2940">使用{column  - &gt;的输入函数或dict的聚合</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2941"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.all.html#pandas.core.groupby.DataFrameGroupBy.all" title="pandas.core.groupby.DataFrameGroupBy.all"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.all</span></code></a>（[axis，bool_only，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2942">返回所有元素是否超过请求的轴的True</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2943"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.any.html#pandas.core.groupby.DataFrameGroupBy.any" title="pandas.core.groupby.DataFrameGroupBy.any"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.any</span></code></a>（[axis，bool_only，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2944">返回任何元素是否超过请求的轴为True</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2945"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.bfill.html#pandas.core.groupby.DataFrameGroupBy.bfill" title="pandas.core.groupby.DataFrameGroupBy.bfill"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.bfill</span></code></a>（[limit]）</span></td>
<td><span class="yiyi-st" id="yiyi-2946">向后填充值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2947"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.corr.html#pandas.core.groupby.DataFrameGroupBy.corr" title="pandas.core.groupby.DataFrameGroupBy.corr"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.corr</span></code></a>（[method，min_periods]）</span></td>
<td><span class="yiyi-st" id="yiyi-2948">计算列的成对相关性，不包括NA /空值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2949"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.count.html#pandas.core.groupby.DataFrameGroupBy.count" title="pandas.core.groupby.DataFrameGroupBy.count"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.count</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2950">计算组的计数，不包括缺少的值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2951"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.cov.html#pandas.core.groupby.DataFrameGroupBy.cov" title="pandas.core.groupby.DataFrameGroupBy.cov"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.cov</span></code></a>（[min_periods]）</span></td>
<td><span class="yiyi-st" id="yiyi-2952">计算列的成对协方差，不包括NA /空值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2953"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.cummax.html#pandas.core.groupby.DataFrameGroupBy.cummax" title="pandas.core.groupby.DataFrameGroupBy.cummax"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.cummax</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-2954">返回请求轴上的累积最大值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2955"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.cummin.html#pandas.core.groupby.DataFrameGroupBy.cummin" title="pandas.core.groupby.DataFrameGroupBy.cummin"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.cummin</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-2956">返回所请求轴上的累积最小值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2957"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.cumprod.html#pandas.core.groupby.DataFrameGroupBy.cumprod" title="pandas.core.groupby.DataFrameGroupBy.cumprod"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.cumprod</span></code></a>（[axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2958">每组的累积积</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2959"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.cumsum.html#pandas.core.groupby.DataFrameGroupBy.cumsum" title="pandas.core.groupby.DataFrameGroupBy.cumsum"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.cumsum</span></code></a>（[axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2960">每组的累计和</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2961"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.describe.html#pandas.core.groupby.DataFrameGroupBy.describe" title="pandas.core.groupby.DataFrameGroupBy.describe"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.describe</span></code></a>（[percentiles，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2962">生成各种汇总统计，不包括NaN值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2963"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.diff.html#pandas.core.groupby.DataFrameGroupBy.diff" title="pandas.core.groupby.DataFrameGroupBy.diff"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.diff</span></code></a>（[periods，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2964">对象的第一离散差异</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2965"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.ffill.html#pandas.core.groupby.DataFrameGroupBy.ffill" title="pandas.core.groupby.DataFrameGroupBy.ffill"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.ffill</span></code></a>（[limit]）</span></td>
<td><span class="yiyi-st" id="yiyi-2966">向前填充值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2967"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.fillna.html#pandas.core.groupby.DataFrameGroupBy.fillna" title="pandas.core.groupby.DataFrameGroupBy.fillna"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.fillna</span></code></a>（[value，method，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2968">使用指定的方法填充NA / NaN值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2969"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.hist.html#pandas.core.groupby.DataFrameGroupBy.hist" title="pandas.core.groupby.DataFrameGroupBy.hist"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.hist</span></code></a>（data [，column，by，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2970">使用matplotlib / pylab绘制DataFrame系列的直方图。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2971"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.idxmax.html#pandas.core.groupby.DataFrameGroupBy.idxmax" title="pandas.core.groupby.DataFrameGroupBy.idxmax"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.idxmax</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-2972">在请求的轴上的第一次出现的最大值的返回索引。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2973"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.idxmin.html#pandas.core.groupby.DataFrameGroupBy.idxmin" title="pandas.core.groupby.DataFrameGroupBy.idxmin"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.idxmin</span></code></a>（[axis，skipna]）</span></td>
<td><span class="yiyi-st" id="yiyi-2974">请求轴上的第一次出现的最小值的返回索引。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2975"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.mad.html#pandas.core.groupby.DataFrameGroupBy.mad" title="pandas.core.groupby.DataFrameGroupBy.mad"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.mad</span></code></a>（[axis，skipna，level]）</span></td>
<td><span class="yiyi-st" id="yiyi-2976">返回请求轴的值的平均绝对偏差</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2977"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.pct_change.html#pandas.core.groupby.DataFrameGroupBy.pct_change" title="pandas.core.groupby.DataFrameGroupBy.pct_change"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.pct_change</span></code></a>（[periods，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2978">给定周期数的百分比变化。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2979"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.plot.html#pandas.core.groupby.DataFrameGroupBy.plot" title="pandas.core.groupby.DataFrameGroupBy.plot"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.plot</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-2980">实现groupby对象的.plot属性的类</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2981"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.quantile.html#pandas.core.groupby.DataFrameGroupBy.quantile" title="pandas.core.groupby.DataFrameGroupBy.quantile"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.quantile</span></code></a>（[q，axis，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2982">在给定分位数的返回值超过请求的轴，一个数字。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2983"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.rank.html#pandas.core.groupby.DataFrameGroupBy.rank" title="pandas.core.groupby.DataFrameGroupBy.rank"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.rank</span></code></a>（[axis，method，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2984">沿轴计算数值数据（1到n）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2985"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.resample.html#pandas.core.groupby.DataFrameGroupBy.resample" title="pandas.core.groupby.DataFrameGroupBy.resample"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.resample</span></code></a>（rule，\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2986">在使用TimeGrouper时提供重新采样</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2987"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.shift.html#pandas.core.groupby.DataFrameGroupBy.shift" title="pandas.core.groupby.DataFrameGroupBy.shift"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.shift</span></code></a>（[periods，freq，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2988">通过周期观察来移动每个组</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2989"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.size.html#pandas.core.groupby.DataFrameGroupBy.size" title="pandas.core.groupby.DataFrameGroupBy.size"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.size</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-2990">计算组大小</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2991"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.skew.html#pandas.core.groupby.DataFrameGroupBy.skew" title="pandas.core.groupby.DataFrameGroupBy.skew"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.skew</span></code></a>（[axis，skipna，level，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2992">返回所请求轴的无偏斜</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-2993"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.take.html#pandas.core.groupby.DataFrameGroupBy.take" title="pandas.core.groupby.DataFrameGroupBy.take"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.take</span></code></a>（indices [，axis，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-2994">类似于ndarray.take</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2995"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.tshift.html#pandas.core.groupby.DataFrameGroupBy.tshift" title="pandas.core.groupby.DataFrameGroupBy.tshift"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.tshift</span></code></a>（[periods，freq，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-2996">移动时间索引，使用索引的频率（如果可用）。</span></td>
</tr>
</tbody>
</table>
<p><span class="yiyi-st" id="yiyi-2997">以下方法仅适用于<code class="docutils literal"><span class="pre">SeriesGroupBy</span></code>对象。</span></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-2998"><a class="reference internal" href="generated/pandas.core.groupby.SeriesGroupBy.nlargest.html#pandas.core.groupby.SeriesGroupBy.nlargest" title="pandas.core.groupby.SeriesGroupBy.nlargest"><code class="xref py py-obj docutils literal"><span class="pre">SeriesGroupBy.nlargest</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-2999">返回最大的<cite>n</cite>元素。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3000"><a class="reference internal" href="generated/pandas.core.groupby.SeriesGroupBy.nsmallest.html#pandas.core.groupby.SeriesGroupBy.nsmallest" title="pandas.core.groupby.SeriesGroupBy.nsmallest"><code class="xref py py-obj docutils literal"><span class="pre">SeriesGroupBy.nsmallest</span></code></a>（\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-3001">返回最小的<cite>n</cite>元素。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3002"><a class="reference internal" href="generated/pandas.core.groupby.SeriesGroupBy.nunique.html#pandas.core.groupby.SeriesGroupBy.nunique" title="pandas.core.groupby.SeriesGroupBy.nunique"><code class="xref py py-obj docutils literal"><span class="pre">SeriesGroupBy.nunique</span></code></a>（[dropna]）</span></td>
<td><span class="yiyi-st" id="yiyi-3003">返回组中唯一元素的数量</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3004"><a class="reference internal" href="generated/pandas.core.groupby.SeriesGroupBy.unique.html#pandas.core.groupby.SeriesGroupBy.unique" title="pandas.core.groupby.SeriesGroupBy.unique"><code class="xref py py-obj docutils literal"><span class="pre">SeriesGroupBy.unique</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-3005">返回对象中的唯一值的np.ndarray。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3006"><a class="reference internal" href="generated/pandas.core.groupby.SeriesGroupBy.value_counts.html#pandas.core.groupby.SeriesGroupBy.value_counts" title="pandas.core.groupby.SeriesGroupBy.value_counts"><code class="xref py py-obj docutils literal"><span class="pre">SeriesGroupBy.value_counts</span></code></a>（[normalize，...]）</span></td>
<td></td>
</tr>
</tbody>
</table>
<p><span class="yiyi-st" id="yiyi-3007">以下方法仅适用于<code class="docutils literal"><span class="pre">DataFrameGroupBy</span></code>对象。</span></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3008"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.corrwith.html#pandas.core.groupby.DataFrameGroupBy.corrwith" title="pandas.core.groupby.DataFrameGroupBy.corrwith"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.corrwith</span></code></a>（other [，axis，drop]）</span></td>
<td><span class="yiyi-st" id="yiyi-3009">计算两个DataFrame对象的行或列之间的成对相关性。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3010"><a class="reference internal" href="generated/pandas.core.groupby.DataFrameGroupBy.boxplot.html#pandas.core.groupby.DataFrameGroupBy.boxplot" title="pandas.core.groupby.DataFrameGroupBy.boxplot"><code class="xref py py-obj docutils literal"><span class="pre">DataFrameGroupBy.boxplot</span></code></a>（已分组[，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-3011">从DataFrameGroupBy数据创建框图。</span></td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section" id="resampling">
<h2><span class="yiyi-st" id="yiyi-3012">重采样</span></h2>
<p><span class="yiyi-st" id="yiyi-3013">重新取样器对象通过重新取样调用返回：<a class="reference internal" href="generated/pandas.DataFrame.resample.html#pandas.DataFrame.resample" title="pandas.DataFrame.resample"><code class="xref py py-func docutils literal"><span class="pre">pandas.DataFrame.resample()</span></code></a>，<a class="reference internal" href="generated/pandas.Series.resample.html#pandas.Series.resample" title="pandas.Series.resample"><code class="xref py py-func docutils literal"><span class="pre">pandas.Series.resample()</span></code></a>。</span></p>
<div class="section" id="id36">
<h3><span class="yiyi-st" id="yiyi-3014">索引，迭代</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3015"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.__iter__.html#pandas.tseries.resample.Resampler.__iter__" title="pandas.tseries.resample.Resampler.__iter__"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.__iter__</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-3016">Groupby迭代器</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3017"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.groups.html#pandas.tseries.resample.Resampler.groups" title="pandas.tseries.resample.Resampler.groups"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.groups</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-3018">dict {group name  - &gt; group labels}</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3019"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.indices.html#pandas.tseries.resample.Resampler.indices" title="pandas.tseries.resample.Resampler.indices"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.indices</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-3020">dict {group name  - &gt; group indices}</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3021"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.get_group.html#pandas.tseries.resample.Resampler.get_group" title="pandas.tseries.resample.Resampler.get_group"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.get_group</span></code></a>（name [，obj]）</span></td>
<td><span class="yiyi-st" id="yiyi-3022">从提供的名称的组构造NDFrame</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id37">
<h3><span class="yiyi-st" id="yiyi-3023">功能应用</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3024"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.apply.html#pandas.tseries.resample.Resampler.apply" title="pandas.tseries.resample.Resampler.apply"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.apply</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-3025">对重采样组应用聚合函数或函数，产生</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3026"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.aggregate.html#pandas.tseries.resample.Resampler.aggregate" title="pandas.tseries.resample.Resampler.aggregate"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.aggregate</span></code></a>（arg，\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-3027">对重采样组应用聚合函数或函数，产生</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3028"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.transform.html#pandas.tseries.resample.Resampler.transform" title="pandas.tseries.resample.Resampler.transform"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.transform</span></code></a>（arg，\ * args，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-3029">调用函数在每个组上产生一个类似索引的系列并返回</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="upsampling">
<h3><span class="yiyi-st" id="yiyi-3030">上采样</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3031"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.ffill.html#pandas.tseries.resample.Resampler.ffill" title="pandas.tseries.resample.Resampler.ffill"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.ffill</span></code></a>（[limit]）</span></td>
<td><span class="yiyi-st" id="yiyi-3032">向前填充值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3033"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.backfill.html#pandas.tseries.resample.Resampler.backfill" title="pandas.tseries.resample.Resampler.backfill"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.backfill</span></code></a>（[limit]）</span></td>
<td><span class="yiyi-st" id="yiyi-3034">向后填充值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3035"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.bfill.html#pandas.tseries.resample.Resampler.bfill" title="pandas.tseries.resample.Resampler.bfill"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.bfill</span></code></a>（[limit]）</span></td>
<td><span class="yiyi-st" id="yiyi-3036">向后填充值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3037"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.pad.html#pandas.tseries.resample.Resampler.pad" title="pandas.tseries.resample.Resampler.pad"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.pad</span></code></a>（[limit]）</span></td>
<td><span class="yiyi-st" id="yiyi-3038">向前填充值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3039"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.fillna.html#pandas.tseries.resample.Resampler.fillna" title="pandas.tseries.resample.Resampler.fillna"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.fillna</span></code></a>（method [，limit]）</span></td>
<td><span class="yiyi-st" id="yiyi-3040">填充缺少的值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3041"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.asfreq.html#pandas.tseries.resample.Resampler.asfreq" title="pandas.tseries.resample.Resampler.asfreq"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.asfreq</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-3042">返回新freq的值，</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3043"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.interpolate.html#pandas.tseries.resample.Resampler.interpolate" title="pandas.tseries.resample.Resampler.interpolate"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.interpolate</span></code></a>（[method，axis，limit，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-3044">根据不同的方法内插值。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="id38">
<h3><span class="yiyi-st" id="yiyi-3045">计算/描述性统计</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3046"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.count.html#pandas.tseries.resample.Resampler.count" title="pandas.tseries.resample.Resampler.count"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.count</span></code></a>（[_ method]）</span></td>
<td><span class="yiyi-st" id="yiyi-3047">计算组的计数，不包括缺少的值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3048"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.nunique.html#pandas.tseries.resample.Resampler.nunique" title="pandas.tseries.resample.Resampler.nunique"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.nunique</span></code></a>（[_ method]）</span></td>
<td><span class="yiyi-st" id="yiyi-3049">返回组中唯一元素的数量</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3050"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.first.html#pandas.tseries.resample.Resampler.first" title="pandas.tseries.resample.Resampler.first"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.first</span></code></a>（[_ method]）</span></td>
<td><span class="yiyi-st" id="yiyi-3051">计算组值的第一个值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3052"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.last.html#pandas.tseries.resample.Resampler.last" title="pandas.tseries.resample.Resampler.last"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.last</span></code></a>（[_ method]）</span></td>
<td><span class="yiyi-st" id="yiyi-3053">计算组值的最后一个</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3054"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.max.html#pandas.tseries.resample.Resampler.max" title="pandas.tseries.resample.Resampler.max"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.max</span></code></a>（[_ method]）</span></td>
<td><span class="yiyi-st" id="yiyi-3055">计算组值的最大值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3056"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.mean.html#pandas.tseries.resample.Resampler.mean" title="pandas.tseries.resample.Resampler.mean"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.mean</span></code></a>（[_ method]）</span></td>
<td><span class="yiyi-st" id="yiyi-3057">计算组的平均值，不包括缺少的值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3058"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.median.html#pandas.tseries.resample.Resampler.median" title="pandas.tseries.resample.Resampler.median"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.median</span></code></a>（[_ method]）</span></td>
<td><span class="yiyi-st" id="yiyi-3059">计算组的中间值，不包括缺失值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3060"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.min.html#pandas.tseries.resample.Resampler.min" title="pandas.tseries.resample.Resampler.min"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.min</span></code></a>（[_ method]）</span></td>
<td><span class="yiyi-st" id="yiyi-3061">计算组值的最小值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3062"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.ohlc.html#pandas.tseries.resample.Resampler.ohlc" title="pandas.tseries.resample.Resampler.ohlc"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.ohlc</span></code></a>（[_ method]）</span></td>
<td><span class="yiyi-st" id="yiyi-3063">计算值的总和，不包括缺少的值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3064"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.prod.html#pandas.tseries.resample.Resampler.prod" title="pandas.tseries.resample.Resampler.prod"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.prod</span></code></a>（[_ method]）</span></td>
<td><span class="yiyi-st" id="yiyi-3065">计算组值的prod</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3066"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.size.html#pandas.tseries.resample.Resampler.size" title="pandas.tseries.resample.Resampler.size"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.size</span></code></a>（[_ method]）</span></td>
<td><span class="yiyi-st" id="yiyi-3067">计算组大小</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3068"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.sem.html#pandas.tseries.resample.Resampler.sem" title="pandas.tseries.resample.Resampler.sem"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.sem</span></code></a>（[_ method]）</span></td>
<td><span class="yiyi-st" id="yiyi-3069">计算组平均值的标准误差，不包括缺失值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3070"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.std.html#pandas.tseries.resample.Resampler.std" title="pandas.tseries.resample.Resampler.std"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.std</span></code></a>（[ddof]）</span></td>
<td><span class="yiyi-st" id="yiyi-3071">计算组的标准偏差，不包括缺失值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3072"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.sum.html#pandas.tseries.resample.Resampler.sum" title="pandas.tseries.resample.Resampler.sum"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.sum</span></code></a>（[_ method]）</span></td>
<td><span class="yiyi-st" id="yiyi-3073">计算组值的总和</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3074"><a class="reference internal" href="generated/pandas.tseries.resample.Resampler.var.html#pandas.tseries.resample.Resampler.var" title="pandas.tseries.resample.Resampler.var"><code class="xref py py-obj docutils literal"><span class="pre">Resampler.var</span></code></a>（[ddof]）</span></td>
<td><span class="yiyi-st" id="yiyi-3075">计算组的方差，不包括缺少的值</span></td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section" id="style">
<h2><span class="yiyi-st" id="yiyi-3076">风格</span></h2>
<p><span class="yiyi-st" id="yiyi-3077"><code class="docutils literal"><span class="pre">Styler</span></code>对象由<a class="reference internal" href="generated/pandas.DataFrame.style.html#pandas.DataFrame.style" title="pandas.DataFrame.style"><code class="xref py py-attr docutils literal"><span class="pre">pandas.DataFrame.style</span></code></a>返回。</span></p>
<div class="section" id="id39">
<h3><span class="yiyi-st" id="yiyi-3078">构造</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3079"><a class="reference internal" href="generated/pandas.formats.style.Styler.html#pandas.formats.style.Styler" title="pandas.formats.style.Styler"><code class="xref py py-obj docutils literal"><span class="pre">Styler</span></code></a>（data [，precision，table_styles，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-3080">帮助根据HTML和CSS的数据样式化DataFrame或Series。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="style-application">
<h3><span class="yiyi-st" id="yiyi-3081">样式申请</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3082"><a class="reference internal" href="generated/pandas.formats.style.Styler.apply.html#pandas.formats.style.Styler.apply" title="pandas.formats.style.Styler.apply"><code class="xref py py-obj docutils literal"><span class="pre">Styler.apply</span></code></a>（func [，axis，subset]）</span></td>
<td><span class="yiyi-st" id="yiyi-3083">应用函数逐列，逐行或表格式，用结果更新HTML表示。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3084"><a class="reference internal" href="generated/pandas.formats.style.Styler.applymap.html#pandas.formats.style.Styler.applymap" title="pandas.formats.style.Styler.applymap"><code class="xref py py-obj docutils literal"><span class="pre">Styler.applymap</span></code></a>（func [，subset]）</span></td>
<td><span class="yiyi-st" id="yiyi-3085">以元素方式应用函数，使用结果更新HTML表示。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3086"><a class="reference internal" href="generated/pandas.formats.style.Styler.format.html#pandas.formats.style.Styler.format" title="pandas.formats.style.Styler.format"><code class="xref py py-obj docutils literal"><span class="pre">Styler.format</span></code></a>（formatter [，subset]）</span></td>
<td><span class="yiyi-st" id="yiyi-3087">格式化单元格的文本显示值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3088"><a class="reference internal" href="generated/pandas.formats.style.Styler.set_precision.html#pandas.formats.style.Styler.set_precision" title="pandas.formats.style.Styler.set_precision"><code class="xref py py-obj docutils literal"><span class="pre">Styler.set_precision</span></code></a>（precision）</span></td>
<td><span class="yiyi-st" id="yiyi-3089">设置用于呈现的精度。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3090"><a class="reference internal" href="generated/pandas.formats.style.Styler.set_table_styles.html#pandas.formats.style.Styler.set_table_styles" title="pandas.formats.style.Styler.set_table_styles"><code class="xref py py-obj docutils literal"><span class="pre">Styler.set_table_styles</span></code></a>（table_styles）</span></td>
<td><span class="yiyi-st" id="yiyi-3091">在Styler上设置表样式。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3092"><a class="reference internal" href="generated/pandas.formats.style.Styler.set_caption.html#pandas.formats.style.Styler.set_caption" title="pandas.formats.style.Styler.set_caption"><code class="xref py py-obj docutils literal"><span class="pre">Styler.set_caption</span></code></a>（caption）</span></td>
<td><span class="yiyi-st" id="yiyi-3093">查看Styler上的标题</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3094"><a class="reference internal" href="generated/pandas.formats.style.Styler.set_properties.html#pandas.formats.style.Styler.set_properties" title="pandas.formats.style.Styler.set_properties"><code class="xref py py-obj docutils literal"><span class="pre">Styler.set_properties</span></code></a>（[subset]）</span></td>
<td><span class="yiyi-st" id="yiyi-3095">Convience方法用于设置一个或多个非数据相关属性或每个单元格。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3096"><a class="reference internal" href="generated/pandas.formats.style.Styler.set_uuid.html#pandas.formats.style.Styler.set_uuid" title="pandas.formats.style.Styler.set_uuid"><code class="xref py py-obj docutils literal"><span class="pre">Styler.set_uuid</span></code></a>（uuid）</span></td>
<td><span class="yiyi-st" id="yiyi-3097">设置样式器的uuid。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3098"><a class="reference internal" href="generated/pandas.formats.style.Styler.clear.html#pandas.formats.style.Styler.clear" title="pandas.formats.style.Styler.clear"><code class="xref py py-obj docutils literal"><span class="pre">Styler.clear</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-3099">“重置”样式器，删除任何以前应用的样式。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="builtin-styles">
<h3><span class="yiyi-st" id="yiyi-3100">内置样式</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3101"><a class="reference internal" href="generated/pandas.formats.style.Styler.highlight_max.html#pandas.formats.style.Styler.highlight_max" title="pandas.formats.style.Styler.highlight_max"><code class="xref py py-obj docutils literal"><span class="pre">Styler.highlight_max</span></code></a>（[subset，color，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-3102">通过阴影背景突出显示最大值</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3103"><a class="reference internal" href="generated/pandas.formats.style.Styler.highlight_min.html#pandas.formats.style.Styler.highlight_min" title="pandas.formats.style.Styler.highlight_min"><code class="xref py py-obj docutils literal"><span class="pre">Styler.highlight_min</span></code></a>（[子集，颜色，轴]）</span></td>
<td><span class="yiyi-st" id="yiyi-3104">通过阴影背景突出显示最小值</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3105"><a class="reference internal" href="generated/pandas.formats.style.Styler.highlight_null.html#pandas.formats.style.Styler.highlight_null" title="pandas.formats.style.Styler.highlight_null"><code class="xref py py-obj docutils literal"><span class="pre">Styler.highlight_null</span></code></a>（[null_color]）</span></td>
<td><span class="yiyi-st" id="yiyi-3106">对背景<code class="docutils literal"><span class="pre">null_color</span></code>进行阴影处理，以查找缺失值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3107"><a class="reference internal" href="generated/pandas.formats.style.Styler.background_gradient.html#pandas.formats.style.Styler.background_gradient" title="pandas.formats.style.Styler.background_gradient"><code class="xref py py-obj docutils literal"><span class="pre">Styler.background_gradient</span></code></a>（[cmap，low，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-3108">根据每列（可选行）中的数据以渐变颜色背景。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3109"><a class="reference internal" href="generated/pandas.formats.style.Styler.bar.html#pandas.formats.style.Styler.bar" title="pandas.formats.style.Styler.bar"><code class="xref py py-obj docutils literal"><span class="pre">Styler.bar</span></code></a>（[subset，axis，color，width]）</span></td>
<td><span class="yiyi-st" id="yiyi-3110">为每列中的值颜色背景<code class="docutils literal"><span class="pre">color</span></code>。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="style-export-and-import">
<h3><span class="yiyi-st" id="yiyi-3111">风格导出导入</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3112"><a class="reference internal" href="generated/pandas.formats.style.Styler.render.html#pandas.formats.style.Styler.render" title="pandas.formats.style.Styler.render"><code class="xref py py-obj docutils literal"><span class="pre">Styler.render</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-3113">将构建的样式呈现为HTML</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3114"><a class="reference internal" href="generated/pandas.formats.style.Styler.export.html#pandas.formats.style.Styler.export" title="pandas.formats.style.Styler.export"><code class="xref py py-obj docutils literal"><span class="pre">Styler.export</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-3115">导出样式以应用于当前Styler。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3116"><a class="reference internal" href="generated/pandas.formats.style.Styler.use.html#pandas.formats.style.Styler.use" title="pandas.formats.style.Styler.use"><code class="xref py py-obj docutils literal"><span class="pre">Styler.use</span></code></a>（styles）</span></td>
<td><span class="yiyi-st" id="yiyi-3117">在当前Styler上设置样式，可能使用<code class="docutils literal"><span class="pre">Styler.export</span></code>的样式。</span></td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section" id="general-utility-functions">
<h2><span class="yiyi-st" id="yiyi-3118">一般效用函数</span></h2>
<div class="section" id="working-with-options">
<h3><span class="yiyi-st" id="yiyi-3119">使用选项</span></h3>
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<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3120"><a class="reference internal" href="generated/pandas.describe_option.html#pandas.describe_option" title="pandas.describe_option"><code class="xref py py-obj docutils literal"><span class="pre">describe_option</span></code></a>（pat [，_print_desc]）</span></td>
<td><span class="yiyi-st" id="yiyi-3121">打印一个或多个注册选项的说明。</span></td>
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<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3122"><a class="reference internal" href="generated/pandas.reset_option.html#pandas.reset_option" title="pandas.reset_option"><code class="xref py py-obj docutils literal"><span class="pre">reset_option</span></code></a>（pat）</span></td>
<td><span class="yiyi-st" id="yiyi-3123">将一个或多个选项重置为其默认值。</span></td>
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<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3124"><a class="reference internal" href="generated/pandas.get_option.html#pandas.get_option" title="pandas.get_option"><code class="xref py py-obj docutils literal"><span class="pre">get_option</span></code></a>（pat）</span></td>
<td><span class="yiyi-st" id="yiyi-3125">检索指定选项的值。</span></td>
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<tr class="row-even"><td><span class="yiyi-st" id="yiyi-3126"><a class="reference internal" href="generated/pandas.set_option.html#pandas.set_option" title="pandas.set_option"><code class="xref py py-obj docutils literal"><span class="pre">set_option</span></code></a>（pat，value）</span></td>
<td><span class="yiyi-st" id="yiyi-3127">设置指定选项的值。</span></td>
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<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-3128"><a class="reference internal" href="generated/pandas.option_context.html#pandas.option_context" title="pandas.option_context"><code class="xref py py-obj docutils literal"><span class="pre">option_context</span></code></a>（\ * args）</span></td>
<td><span class="yiyi-st" id="yiyi-3129">上下文管理器临时设置<cite>与</cite>语句上下文中的选项。</span></td>
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